Triple
T1506245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbara McLean |
E33907
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Wilson
"Wilson" is a 1944 American biographical film about U.S. President Woodrow Wilson, noted for its ambitious production and multiple Academy Awards.
|
E204059
|
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: Wilson | Statement: [Barbara McLean, notableWork, Wilson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wilson Context triple: [Barbara McLean, notableWork, Wilson]
-
A.
Wilson
Wilson is a common English-language surname borne by numerous notable figures across fields such as science, politics, sports, and the arts.
-
B.
Wilson
Wilson is a Chicago Transit Authority 'L' station on the North Side that serves as a major stop on the Red Line.
-
C.
Williams
Williams is a common English surname borne by numerous notable figures across sports, politics, arts, and entertainment.
-
D.
Johnson
Johnson is a common English surname borne by numerous notable individuals across politics, arts, sports, and other fields.
-
E.
Howard
Howard is the given first name of Ward Cunningham, the American computer programmer best known for creating the first wiki.
- 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: Wilson Triple: [Barbara McLean, notableWork, Wilson]
Generated description
"Wilson" is a 1944 American biographical film about U.S. President Woodrow Wilson, noted for its ambitious production and multiple Academy Awards.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wilson Target entity description: "Wilson" is a 1944 American biographical film about U.S. President Woodrow Wilson, noted for its ambitious production and multiple Academy Awards.
-
A.
Wilson
Wilson is a common English-language surname borne by numerous notable figures across fields such as science, politics, sports, and the arts.
-
B.
Wilson
Wilson is a Chicago Transit Authority 'L' station on the North Side that serves as a major stop on the Red Line.
-
C.
Williams
Williams is a common English surname borne by numerous notable figures across sports, politics, arts, and entertainment.
-
D.
Johnson
Johnson is a common English surname borne by numerous notable individuals across politics, arts, sports, and other fields.
-
E.
Howard
Howard is the middle name of Edwin H. Armstrong, the pioneering American electrical engineer and inventor of FM radio.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a88735f8a8819089177a4d3e4a0211 |
completed | March 4, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf3d408881909688667be4a32931 |
completed | March 8, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69adc1942da4819081fdcb4cc4b5f9f2 |
completed | March 8, 2026, 6:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adc225e1ec8190adbc075f44b82419 |
completed | March 8, 2026, 6:38 p.m. |
Created at: March 4, 2026, 7:24 p.m.