Triple
T23362561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rutherford Falls |
E593222
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Dana L. Wilson
Dana L. Wilson is an American actress known for her role in the television comedy series "Rutherford Falls."
|
E1584693
|
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: Dana L. Wilson | Statement: [Rutherford Falls, starring, Dana L. Wilson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dana L. Wilson Context triple: [Rutherford Falls, starring, Dana L. Wilson]
-
A.
Dana H. Crissy
Dana H. Crissy was a U.S. Army aviation officer and early military aviator whose legacy is commemorated by the naming of Crissy Field in San Francisco.
-
B.
Tracy B. Strong
Tracy B. Strong was an American political theorist known for his influential work on Nietzsche, democratic theory, and the history of political thought.
-
C.
Dana E. Glauberman
Dana E. Glauberman is an American film editor known for her work on acclaimed movies such as the indie comedy-drama "Juno."
-
D.
Tracy C. Drake
Tracy C. Drake was an American hotelier best known for developing and operating prominent Chicago luxury hotels in the early 20th century.
-
E.
Kendra L. Wilson
Kendra L. Wilson is a film producer known for her work on the Bruce Lee–inspired martial arts drama "Birth of the Dragon."
- 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: Dana L. Wilson Triple: [Rutherford Falls, starring, Dana L. Wilson]
Generated description
Dana L. Wilson is an American actress known for her role in the television comedy series "Rutherford Falls."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dana L. Wilson Target entity description: Dana L. Wilson is an American actress known for her role in the television comedy series "Rutherford Falls."
-
A.
Dana H. Crissy
Dana H. Crissy was a U.S. Army aviation officer and early military aviator whose legacy is commemorated by the naming of Crissy Field in San Francisco.
-
B.
Tracy B. Strong
Tracy B. Strong was an American political theorist known for his influential work on Nietzsche, democratic theory, and the history of political thought.
-
C.
Dana E. Glauberman
Dana E. Glauberman is an American film editor known for her work on acclaimed movies such as the indie comedy-drama "Juno."
-
D.
Tracy C. Drake
Tracy C. Drake was an American hotelier best known for developing and operating prominent Chicago luxury hotels in the early 20th century.
-
E.
Kendra L. Wilson
Kendra L. Wilson is a film producer known for her work on the Bruce Lee–inspired martial arts drama "Birth of the Dragon."
- 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0aa0ed88190b0198cbfd1bcc59b |
completed | April 29, 2026, 6:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c5dd5ca4881909453c262d6ab9b1a |
completed | May 19, 2026, 12:55 p.m. |
| NEDg | Description generation | batch_6a0c61cdf14481909173cc65e16f2c82 |
completed | May 19, 2026, 1:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c625b52248190ba3d59f42dd99da3 |
completed | May 19, 2026, 1:15 p.m. |
Created at: April 17, 2026, 5:30 p.m.