Triple
T25115681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burari |
E629121
|
entity |
| Predicate | hasNearbyRecreationalSite |
P68166
|
FINISHED |
| Object | Coronation Park, Delhi |
—
|
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: Coronation Park, Delhi | Statement: [Burari, hasNearbyRecreationalSite, Coronation Park, Delhi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyRecreationalSite Context triple: [Burari, hasNearbyRecreationalSite, Coronation Park, Delhi]
-
A.
hasRecreationalActivityNearby
Indicates that a location has one or more recreational activities or facilities available in its nearby surroundings.
-
B.
hasRecreationalUseNearby
chosen
Indicates that there is at least one location or facility for recreational activities situated close to the referenced entity.
-
C.
hasNearbyStatePark
Indicates that a location is situated close to at least one designated state park.
-
D.
hasNearbyProvincialPark
Indicates that one entity is located close to, or in the vicinity of, a provincial park.
-
E.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
- 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_69e2ff3169d08190973b6061d5009abd |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 18, 2026, 6:27 a.m.