Triple
T30159617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Redfern Avenue, Gillingham, Kent |
E766624
|
entity |
| Predicate | hasNearbySportsFacility |
P104350
|
FINISHED |
| Object | Priestfield Stadium |
—
|
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: Priestfield Stadium | Statement: [Redfern Avenue, Gillingham, Kent, hasNearbySportsFacility, Priestfield Stadium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbySportsFacility Context triple: [Redfern Avenue, Gillingham, Kent, hasNearbySportsFacility, Priestfield Stadium]
-
A.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
B.
hasNearbyStadium
chosen
Indicates that one entity is located close to or in the vicinity of a stadium associated with another entity.
-
C.
hasRecreationalActivityNearby
Indicates that a location has one or more recreational activities or facilities available in its nearby surroundings.
-
D.
hasRecreationalUseNearby
Indicates that there is at least one location or facility for recreational activities situated close to the referenced entity.
-
E.
nearRetailPark
Indicates that one entity is located close to or in the immediate vicinity of a retail park.
- 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_69f2247a968881909d79c18f2bfcb275 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe991bca608190b524e419642f4243 |
completed | May 9, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69fe979fc1c4819091fc48d63ea12063 |
completed | May 9, 2026, 2:10 a.m. |
Created at: April 29, 2026, 7:21 p.m.