Triple
T4447195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lochgelly Loch |
E96317
|
entity |
| Predicate | nearbyLandUse |
P19783
|
FINISHED |
| Object | former coal mining areas |
—
|
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 coal mining areas | Statement: [Lochgelly Loch, nearbyLandUse, former coal mining areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyLandUse Context triple: [Lochgelly Loch, nearbyLandUse, former coal mining areas]
-
A.
hasNearbyLandUse
chosen
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
B.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
C.
nearbyCurrent
Indicates that one entity is located close to another entity at the present moment or in the current context.
-
D.
nearbyVenue
Indicates that one venue is located close to another venue in physical space.
-
E.
transportationNearby
Indicates that there is a transportation facility or service located close to the referenced entity.
- 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_69b345415ba481908df738e7174448ba |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355d31e10819086590b9f828d50b0 |
completed | March 13, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69b34f62c180819097ced38da2052207 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:32 p.m.