Triple
T13381641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beckets Park |
E319330
|
entity |
| Predicate | distanceToTownCentre |
P1299
|
FINISHED |
| Object | short walking distance |
—
|
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: short walking distance | Statement: [Beckets Park, distanceToTownCentre, short walking distance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTownCentre Context triple: [Beckets Park, distanceToTownCentre, short walking distance]
-
A.
distanceToWokingTownCentre
Indicates the spatial distance between a given location and the center of Woking town.
-
B.
distanceToReadingTownCentre
Indicates the measured distance between a given location and the centre of Reading town.
-
C.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
D.
directionFromCityCentre
Indicates the compass direction in which one location lies relative to the city centre.
-
E.
distanceFromCentralLondon
Indicates the spatial separation or length of travel between a given location and central London.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce694788190881d1feac5b75720 |
completed | April 11, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69d9a03189908190a784a2755f8d81e1 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:33 p.m.