Triple
T918333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Overton |
E19822
|
entity |
| Predicate | isToponymFor |
P19572
|
FINISHED |
| Object | multiple settlements named Overton in England |
—
|
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: multiple settlements named Overton in England | Statement: [Overton, isToponymFor, multiple settlements named Overton in England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isToponymFor Context triple: [Overton, isToponymFor, multiple settlements named Overton in England]
-
A.
isToponymic
Indicates that something is related to or derived from a place name (a toponym).
-
B.
hasToponymicUse
Indicates that a term or name is used as a toponym, i.e., as a place name or geographic designation.
-
C.
hasToponymicForm
Indicates that one entity is a toponymic (place-name-based) form or variant derived from another entity.
-
D.
typeOfToponym
Indicates the specific category or kind of place name (toponym) that applies to a given geographic entity.
-
E.
toponymSourceFor
chosen
Indicates that one entity serves as the origin, basis, or source from which another entity’s place name (toponym) is derived.
- 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_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b388f0bc8190a087222636135ba5 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b2944ff88190a260be5355132ba5 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.