Triple
T23277253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joan Brown |
E588755
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Joan Brown |
—
|
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: Joan Brown | Statement: [Joan Brown, name, Joan Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joan Brown Context triple: [Joan Brown, name, Joan Brown]
-
A.
Joan Brown
chosen
Joan Brown was an influential American figurative painter associated with the Bay Area art scene, known for her bold, autobiographical works blending abstraction and representation.
-
B.
Joan Browne
Joan Browne was the wife of American actor and singer Robert Alda.
-
C.
Joan Pirkle
Joan Pirkle is an American actress known for her film and television roles and for being married to actor Kurtwood Smith.
-
D.
Joan Clayton
Joan Clayton is the ambitious, neurotic yet loving attorney and central protagonist of the TV sitcom "Girlfriends."
-
E.
Joan Evans
Joan Evans was an American film actress active in the 1940s and 1950s, known for her roles in Hollywood dramas and coming-of-age films.
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19578adf48190bdb129a55f86172c |
completed | April 29, 2026, 5:22 a.m. |
Created at: April 17, 2026, 4:49 p.m.