Triple
T18608789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brereton and Ravenhill |
E454829
|
entity |
| Predicate | administrativeAreaLevel |
P92063
|
FINISHED |
| Object | local |
—
|
LITERAL 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: local | Statement: [Brereton and Ravenhill, administrativeAreaLevel, local]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: administrativeAreaLevel Context triple: [Brereton and Ravenhill, administrativeAreaLevel, local]
-
A.
sharesAdministrativeLevel
Indicates that two entities are associated with the same tier or rank within an administrative or governmental hierarchy.
-
B.
hasAdministrativeArea
Indicates that one entity serves as the governing or jurisdictional area responsible for administering another entity.
-
C.
denotesAdministrativeArea
Indicates that one entity designates or specifies another entity as its relevant administrative area or jurisdiction.
-
D.
isPartOfAdministrativeLevel
Indicates that one administrative unit is contained within or belongs to a higher-level administrative division in a governance hierarchy.
-
E.
administrativeTerritoryType
chosen
Indicates the classification of an administrative area according to its level or type of territorial governance (e.g., city, county, province).
- 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54cff3be8819080ab20045bd18a4d |
completed | April 19, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69e478cf5e888190a0b1074b0c6525df |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:45 a.m.