Triple
T10390650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monsters vs. Aliens |
E244883
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object |
Gil Zimmerman
Gil Zimmerman is a cinematographer best known for his work on the animated feature film "Monsters vs. Aliens."
|
E879313
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Gil Zimmerman | Statement: [Monsters vs. Aliens, cinematographyBy, Gil Zimmerman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gil Zimmerman Context triple: [Monsters vs. Aliens, cinematographyBy, Gil Zimmerman]
-
A.
Don Zimmerman
Don Zimmerman is a film editor known for his work on major Hollywood movies, including the family adventure-comedy "Night at the Museum."
-
B.
Sam Zussman
Sam Zussman is a sports and media executive who serves as a top business leader for the NBA’s Brooklyn Nets organization.
-
C.
Dean Zimmerman
Dean Zimmerman is an American film editor known for his work on major Hollywood action and science-fiction films.
-
D.
David Zuckerman
David Zuckerman is an American television producer and writer best known for his work on animated comedy series, including helping develop and produce the hit show Family Guy.
-
E.
Mitch Kertzman
Mitch Kertzman is an American technology executive and entrepreneur best known for his leadership roles in the software and semiconductor industries, including at companies like LSI Logic and Sybase.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gil Zimmerman Triple: [Monsters vs. Aliens, cinematographyBy, Gil Zimmerman]
Generated description
Gil Zimmerman is a cinematographer best known for his work on the animated feature film "Monsters vs. Aliens."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gil Zimmerman Target entity description: Gil Zimmerman is a cinematographer best known for his work on the animated feature film "Monsters vs. Aliens."
-
A.
Don Zimmerman
Don Zimmerman is a film editor known for his work on major Hollywood movies, including the family adventure-comedy "Night at the Museum."
-
B.
Sam Zussman
Sam Zussman is a sports and media executive who serves as a top business leader for the NBA’s Brooklyn Nets organization.
-
C.
Dean Zimmerman
Dean Zimmerman is an American film editor known for his work on major Hollywood action and science-fiction films.
-
D.
David Zuckerman
David Zuckerman is an American television producer and writer best known for his work on animated comedy series, including helping develop and produce the hit show Family Guy.
-
E.
Mitch Kertzman
Mitch Kertzman is an American technology executive and entrepreneur best known for his leadership roles in the software and semiconductor industries, including at companies like LSI Logic and Sybase.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9b4f7d08190bcb16d3b4c8f22ad |
completed | April 7, 2026, 11:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9881d84588190a9117064a0950ac1 |
completed | April 10, 2026, 11:30 p.m. |
| NEDg | Description generation | batch_69d98ae8403c81908a229aa06bd0388a |
completed | April 10, 2026, 11:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d98ce9ba0c8190a7c62fa670e23705 |
completed | April 10, 2026, 11:51 p.m. |
Created at: April 6, 2026, 12:06 p.m.