Triple
T12096504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pewsey |
E288083
|
entity |
| Predicate | hasHistoricMarketTownCharacter |
P17485
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Pewsey, hasHistoricMarketTownCharacter, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricMarketTownCharacter Context triple: [Pewsey, hasHistoricMarketTownCharacter, true]
-
A.
hasMarketTownHistory
chosen
Indicates that an entity has a historical association with functioning as a market town or possessing recognized market-town status in the past.
-
B.
containsHistoricTown
Indicates that one entity geographically includes or encompasses a town that has recognized historical significance.
-
C.
historicalTownshipOf
Indicates that one entity was formerly a township encompassing or governing the other entity during a past historical period.
-
D.
hasCastleTownHistory
Indicates that an entity has a historical association with a castle town, such as originating from, being located in, or significantly shaped by one.
-
E.
hasMarketTownStatus
Indicates that a settlement holds the official legal or historical status of being recognized as a market town.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9178ad99c8190a54777b9bbe998bc |
completed | April 10, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69d915000454819089fee00022055599 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:48 p.m.