Triple
T20938979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pig (2021 film) |
E515663
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object |
Philip Klein
Philip Klein is a film composer known for scoring movies such as the 2021 animated feature "Pig."
|
E1458194
|
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: Philip Klein | Statement: [Pig (2021 film), musicBy, Philip Klein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Philip Klein Context triple: [Pig (2021 film), musicBy, Philip Klein]
-
A.
Philip Klein
Philip Klein was an American screenwriter active during the early 20th century, known for his work on silent and early sound films.
-
B.
David S. Johnson
David S. Johnson was a prominent American computer scientist known for his influential work in algorithms and computational complexity, particularly in the study of NP-completeness and approximation algorithms.
-
C.
Eli Upfal
Eli Upfal is a computer scientist known for his contributions to randomized algorithms, probabilistic analysis, and theoretical computer science.
-
D.
David P. Dobkin
David P. Dobkin is an American film director and producer best known for directing the comedy hit "Wedding Crashers."
-
E.
S. Rao Kosaraju
S. Rao Kosaraju is a computer scientist known for his contributions to algorithm design and graph theory, including early work on strongly connected components algorithms.
- 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: Philip Klein Triple: [Pig (2021 film), musicBy, Philip Klein]
Generated description
Philip Klein is a film composer known for scoring movies such as the 2021 animated feature "Pig."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Philip Klein Target entity description: Philip Klein is a film composer known for scoring movies such as the 2021 animated feature "Pig."
-
A.
Philip Klein
Philip Klein was an American screenwriter active during the early 20th century, known for his work on silent and early sound films.
-
B.
David S. Johnson
David S. Johnson was a prominent American computer scientist known for his influential work in algorithms and computational complexity, particularly in the study of NP-completeness and approximation algorithms.
-
C.
Eli Upfal
Eli Upfal is a computer scientist known for his contributions to randomized algorithms, probabilistic analysis, and theoretical computer science.
-
D.
David P. Dobkin
David P. Dobkin is an American film director and producer best known for directing the comedy hit "Wedding Crashers."
-
E.
S. Rao Kosaraju
S. Rao Kosaraju is a computer scientist known for his contributions to algorithm design and graph theory, including early work on strongly connected components algorithms.
- 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_69e0b4fc13408190b06868df03c5c29b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f95419a48190b7f62abc59f38bef |
completed | April 21, 2026, 4:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a091fd65840819085742a8c45a8a012 |
completed | May 17, 2026, 1:54 a.m. |
| NEDg | Description generation | batch_6a0920c37ec48190a043097a24151022 |
completed | May 17, 2026, 1:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09219be3c48190a610062e59e05876 |
completed | May 17, 2026, 2:02 a.m. |
Created at: April 16, 2026, 12:50 p.m.