Triple
T7873847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hailes Abbey |
E182802
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Hailes |
E515799
|
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: Hailes | Statement: [Hailes Abbey, locatedIn, Hailes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hailes Context triple: [Hailes Abbey, locatedIn, Hailes]
-
A.
Hailes
chosen
Hailes is a small historic village in Gloucestershire, England, best known for the ruins of Hailes Abbey and its picturesque Cotswold setting.
-
B.
Hilsea
Hilsea is a northern suburb of Portsmouth on Portsea Island in Hampshire, England, known for its residential areas, military history, and transport links including the Hilsea railway station.
-
C.
Hawise
Hawise is a medieval European female given name borne by several noblewomen in England and France.
-
D.
Hayle
Hayle is a small coastal town and port in west Cornwall, England, situated at the mouth of the Hayle River and known for its industrial heritage and sandy beaches.
-
E.
Kyme
Kyme is an American actress best known for her role as Rachel Meadows in Spike Lee's 1988 film "School Daze."
- 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39a7f1648190980db4db1a800189 |
completed | March 31, 2026, 3:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5b72cec08190ac8ea1d9676b68ce |
completed | March 31, 2026, 5:28 a.m. |
Created at: March 30, 2026, 4:56 p.m.