Triple
T24694115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warwickshire Avon |
E611533
|
entity |
| Predicate | notableSettlementOn |
P3858
|
FINISHED |
| Object | Stratford-upon-Avon |
—
|
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: Stratford-upon-Avon | Statement: [Warwickshire Avon, notableSettlementOn, Stratford-upon-Avon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableSettlementOn Context triple: [Warwickshire Avon, notableSettlementOn, Stratford-upon-Avon]
-
A.
notableSettlementCountry
Indicates that a country is notably associated with a particular settlement, such as being its primary or most recognized national affiliation.
-
B.
notableHumanSettlement
Indicates that a location is recognized as a significant or noteworthy human settlement, such as a city, town, or village.
-
C.
notableRegionOfSettlement
Indicates that a specified region is a significant or prominent place where an entity is or has been settled.
-
D.
notableAsSettingOf
Indicates that a place or environment is recognized as the setting where the events of a particular work (e.g., book, film, story) take place.
-
E.
notableLocation
chosen
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
- F. None of above.
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_69e2c4d76d148190b58ad612467149a5 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f6135293908190809e255bf6334760 |
completed | May 2, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
Created at: April 18, 2026, 3:21 a.m.