Triple
T32893297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Methlick |
E841396
|
entity |
| Predicate | hasNotableNearbySettlement |
P3883
|
FINISHED |
| Object | Gight |
—
|
NE NERFINISHED |
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: Gight | Statement: [Methlick, hasNotableNearbySettlement, Gight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableNearbySettlement Context triple: [Methlick, hasNotableNearbySettlement, Gight]
-
A.
hasNoUrbanSettlement
Indicates that the referenced area or region does not contain any urban settlements such as towns or cities.
-
B.
hasNearestLargerSettlement
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
-
C.
hasNearbyTown
chosen
Indicates that one location has a town situated close to it in geographic proximity.
-
D.
hasNearbySettlementPattern
Indicates that one entity exhibits a settlement distribution or layout that is spatially close to, or clustered around, another entity.
-
E.
distanceFromNearestSettlementKilometers
Indicates the distance, measured in kilometers, from an entity’s location to the closest human settlement.
- 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_69f34945ae408190b72d8118c83beb77 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a016777257081908841c5522dfa76e6 |
completed | May 11, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_6a0164e49bec8190af3c8626be9677a9 |
completed | May 11, 2026, 5:11 a.m. |
Created at: May 1, 2026, 1:18 a.m.