Triple
T13694156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbershop |
E328341
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Mark Brown |
E173417
|
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: Mark Brown | Statement: [Barbershop, writer, Mark Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Brown Context triple: [Barbershop, writer, Mark Brown]
-
A.
Mark Brown
chosen
Mark Brown is an American filmmaker and screenwriter best known for writing and directing the romantic comedy film "Two Can Play That Game."
-
B.
Mark Brown
Mark Brown is a creator known for his work associated with American rapper and actress Shanté Smith, better known as Da Brat.
-
C.
Mark Brown
Mark Brown is a musician best known as a member of Prince’s backing band, The Revolution.
-
D.
Matthew Brown
Matthew Brown is a film director best known for helming the biographical drama "The Man Who Knew Infinity," about mathematician Srinivasa Ramanujan.
-
E.
Matt Brown
Matt Brown is an American mixed martial artist and longtime UFC welterweight known for his aggressive, brawling style and high finishing rate.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8757b648190a26181efbad09a43 |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d4f35888190b2c3df62bde1ce6e |
completed | May 3, 2026, 7:09 p.m. |
Created at: April 9, 2026, 9:54 p.m.