Triple
T7093222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bannister |
E165253
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Bannister |
E165253
|
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: Bannister | Statement: [Bannister, hasName, Bannister]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bannister Context triple: [Bannister, hasName, Bannister]
-
A.
Bannister
chosen
Bannister is a minor juror character in the play "Inherit the Wind," representing the everyday townspeople caught between religious fundamentalism and evolving scientific thought.
-
B.
Fitzherbert
Fitzherbert is a residential suburb located in the city of Palmerston North on New Zealand’s North Island.
-
C.
Fitzherbert
Fitzherbert is an English surname historically associated with notable figures in British politics, diplomacy, and the aristocracy.
-
D.
Bowerman
Bowerman is a surname most prominently associated with Bill Bowerman, the legendary American track coach and co-founder of Nike.
-
E.
Tibbett
Tibbett is a surname of English origin borne by various notable individuals in fields such as music, sports, and the arts.
- 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_69c6887e8c10819091cee237560d32da |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e532513c8190968eea8a0d3235a0 |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79c960484819098228cebccb8c935 |
completed | March 28, 2026, 9:17 a.m. |
Created at: March 27, 2026, 2:41 p.m.