Triple
T20994480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bev |
E517110
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Bev |
—
|
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: Bev | Statement: [Bev, name, Bev]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bev Context triple: [Bev, name, Bev]
-
A.
Bev
chosen
Bev is a central white homeowner in the play "Clybourne Park," whose well-meaning but oblivious attitudes toward race and change highlight the tensions surrounding the sale of her house in a transforming neighborhood.
-
B.
Bevans
Bevans is a surname most notably associated with American character actor Clem Bevans, known for his portrayals of rustic and elderly men in early 20th-century film and theater.
-
C.
Bever
Bever is a small Swiss alpine village and municipality in the canton of Graubünden, known for its traditional Engadine architecture and scenic mountain surroundings.
-
D.
Bever
Bever is a small river in Germany that serves as one of the tributaries feeding into the Weser.
-
E.
Bez
Bez is a British dancer and percussionist best known for his energetic onstage presence with the Madchester band Happy Mondays.
- 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc1e75188190a97114238ea0b4f9 |
completed | April 21, 2026, 4:25 a.m. |
Created at: April 16, 2026, 1:50 p.m.