Triple
T36363169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Llyn Ystradau |
E895548
|
entity |
| Predicate | nearbyTownType |
P65946
|
FINISHED |
| Object | former slate-mining town |
—
|
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: former slate-mining town | Statement: [Llyn Ystradau, nearbyTownType, former slate-mining town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyTownType Context triple: [Llyn Ystradau, nearbyTownType, former slate-mining town]
-
A.
hasNearbyTownType
chosen
Indicates that one entity has, in its vicinity, a town of a specified type or classification.
-
B.
hasNearbyTown
Indicates that one location has a town situated close to it in geographic proximity.
-
C.
nearbySettlements
Indicates that one settlement is located close to another settlement in geographic space.
-
D.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
E.
nearbySettlementRegion
Indicates that a settlement is located close to or within the surrounding area of a specified region.
- 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_69f76e5044248190b390d8887dc03254 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fee25dbca481909e6f1c255122b3a8 |
completed | May 9, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69fee1c8915c8190b08b63e42881f1a9 |
completed | May 9, 2026, 7:27 a.m. |
Created at: May 3, 2026, 4:10 p.m.