Triple
T8324960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Wilson (economist) |
E194927
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wilson |
E4321
|
NE FINISHED |
How this triple was built (2 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: [James Wilson (economist), familyName, Wilson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wilson Context triple: [James Wilson (economist), familyName, Wilson]
-
A.
Wilson
chosen
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 1944 American biographical film about U.S. President Woodrow Wilson, noted for its ambitious production and multiple Academy Awards.
-
C.
Wilson
Wilson is a small city in eastern North Carolina known historically for its tobacco and textile industries and now for its diversified economy and educational institutions.
-
D.
Wilson
Wilson is a city in eastern North Carolina known historically for its tobacco and textile industries and now for its cultural attractions and public gardens.
-
E.
Wilson
Wilson is a well-known American sporting goods manufacturer recognized especially for its basketballs and other professional sports equipment.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82e7a8a88190a32bb5cc0feb012d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f7e4f8081908e0f876ad962c932 |
completed | March 31, 2026, 8:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc6fee5dc8190b2de22d210884e51 |
completed | April 2, 2026, 1:31 a.m. |
Created at: March 30, 2026, 5:56 p.m.