Triple
T4894780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dent, Yorkshire, England |
E109648
|
entity |
| Predicate | distanceToDentStation |
P31869
|
FINISHED |
| Object | approximately 4 miles |
—
|
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: approximately 4 miles | Statement: [Dent, Yorkshire, England, distanceToDentStation, approximately 4 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToDentStation Context triple: [Dent, Yorkshire, England, distanceToDentStation, approximately 4 miles]
-
A.
distanceFromTerminus
Indicates the measured distance of an entity from a defined endpoint or terminus along a route, path, or sequence.
-
B.
operatorOfNearestStation
Indicates that an entity is the organization or operator responsible for managing the station that is geographically closest to a given reference point or entity.
-
C.
distancedFrom
Indicates that one entity is physically or metaphorically kept at a certain distance or separation from another entity.
-
D.
hasNearbyRailwayStation
chosen
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
-
E.
distanceFromReading
Indicates the measured spatial distance between a specified entity and the location of Reading.
- 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffabccc81909115ece1b04e2061 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2e7b5c8190b8bf9d616dfa24f0 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:28 p.m.