Triple
T2978960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bennett |
E80464
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Bennet |
E248244
|
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: Bennet | Statement: [Bennett, hasVariant, Bennet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bennet Context triple: [Bennett, hasVariant, Bennet]
-
A.
Lydia Bennet
Lydia Bennet is the impulsive, flirtatious youngest Bennet sister in Jane Austen’s novel "Pride and Prejudice," whose elopement scandal threatens her family’s reputation.
-
B.
Bingley
Bingley is a historic market town in West Yorkshire, England, known for its industrial heritage and scenic waterways.
-
C.
Mr Bennet
chosen
Mr Bennet is the witty, detached patriarch of the Bennet family in Jane Austen’s novel "Pride and Prejudice."
-
D.
Mirabelle Buttersfield
Mirabelle Buttersfield is the shy, introspective young woman at the center of Steve Martin’s novella and film "Shopgirl," whose quiet life as a department store glove salesgirl is upended by an unexpected romantic entanglement.
-
E.
Anna Scott
Anna Scott is a famous American movie star who becomes romantically involved with a shy British bookseller in the romantic comedy film "Notting Hill."
- 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_69ad8b15f6ac8190be5fd16a33edcb4f |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad999cca40819082e2d6d10bdb7872 |
completed | March 8, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b108ef607c8190865b079beb1b6da5 |
completed | March 11, 2026, 6:17 a.m. |
Created at: March 8, 2026, 2:58 p.m.