Triple
T32882249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Marston, Hertfordshire |
E841094
|
entity |
| Predicate | closestMarketTown |
P145151
|
FINISHED |
| Object | Tring |
—
|
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: Tring | Statement: [Long Marston, Hertfordshire, closestMarketTown, Tring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closestMarketTown Context triple: [Long Marston, Hertfordshire, closestMarketTown, Tring]
-
A.
nearestTownDistance
Indicates the distance from a given location to the closest town.
-
B.
nearestCityTo
Indicates that one city is the closest in distance to a given location or entity compared to all other cities.
-
C.
nearestMajorTowns
Indicates that one or more major towns are the closest significant urban centers to a given location or entity.
-
D.
hasNearestLargerSettlement
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
-
E.
nearestSuburbOrTown
chosen
Indicates that one place is the geographically closest suburb or town to another specified location.
- 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_69f349446e288190a70c05bcc4d81172 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7a225a77c81908f8953ccfeb14336 |
completed | May 3, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 1, 2026, 1:18 a.m.