Triple
T21612696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishop Hannington |
E533350
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hannington |
—
|
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: Hannington | Statement: [Bishop Hannington, familyName, Hannington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hannington Context triple: [Bishop Hannington, familyName, Hannington]
-
A.
Hannington
Hannington is a small rural village in the English county of Hampshire, known for its traditional countryside setting and historic character.
-
B.
Hannington
chosen
Hannington is a small rural village in Wiltshire, England, known for its traditional English countryside setting and historic character.
-
C.
Hellingly
Hellingly is a village and civil parish in East Sussex, England, known for its rural character and historic parish church.
-
D.
Haseldine
Haseldine is the middle name of William Haseldine Pepys, an English scientist and instrument maker active in the late 18th and early 19th centuries.
-
E.
Hawise
Hawise is a medieval European female given name borne by several noblewomen in England and France.
- 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_69e0c46411108190bba0d4176dffc9f3 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef3ba79424819094e9ee93c4bbcc0b |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 16, 2026, 6:33 p.m.