Triple
T22776724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Bradley Wing |
E563722
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Tom Bradley |
—
|
NE NERFINISHED |
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: Tom Bradley | Statement: [Tom Bradley Wing, namedAfter, Tom Bradley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Bradley Context triple: [Tom Bradley Wing, namedAfter, Tom Bradley]
-
A.
Tom Bradley
chosen
Tom Bradley was a long-serving and influential mayor of Los Angeles who played a key role in the city’s late-20th-century growth and international prominence.
-
B.
Tom Bradley
Tom Bradley is the fictional protagonist of the 1936 film "Desire," around whom the movie’s central romantic and dramatic events revolve.
-
C.
Norman Chandler
Norman Chandler was an American newspaper publisher who led the Los Angeles Times to major expansion and influence in the mid-20th century.
-
D.
Coleman A. Young
Coleman A. Young was a pioneering African American politician who served as the long-time mayor of Detroit, Michigan, from 1974 to 1994.
-
E.
Kenneth Hahn
Kenneth Hahn was a long-serving Los Angeles County Supervisor known for his influential role in expanding public services, civil rights advocacy, and developing parks and recreation facilities in the region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24554497c819080b996e071de27c2 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b6260a8819080e57481281dfe40 |
completed | April 29, 2026, 3:30 a.m. |
Created at: April 17, 2026, 3:28 p.m.