Triple
T4669365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hantescire |
E102923
|
entity |
| Predicate | toponymCategory |
P17163
|
FINISHED |
| Object | English county name |
—
|
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: English county name | Statement: [Hantescire, toponymCategory, English county name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toponymCategory Context triple: [Hantescire, toponymCategory, English county name]
-
A.
typeOfToponym
chosen
Indicates the specific category or kind of place name (toponym) that applies to a given geographic entity.
-
B.
isToponymic
Indicates that something is related to or derived from a place name (a toponym).
-
C.
hasToponymicUse
Indicates that a term or name is used as a toponym, i.e., as a place name or geographic designation.
-
D.
hasToponymicDerivatives
Indicates that a name or term serves as the source from which related place-based or toponymic names are derived.
-
E.
cityNamedAfter
Indicates that one city derives its name from or was named in honor of another entity, such as a person, place, or concept.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd655aceb081908100ffc0498fe183 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6215864c8190b50ba0f63ba87d0c |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:15 p.m.