Triple
T25885059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Quadrilateral |
E652164
|
entity |
| Predicate | hasCityVertex |
P26386
|
FINISHED |
| Object | 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: Delhi | Statement: [Golden Quadrilateral, hasCityVertex, Delhi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCityVertex Context triple: [Golden Quadrilateral, hasCityVertex, Delhi]
-
A.
hasCityStatusFor
Indicates that an entity holds official city status within the jurisdiction or context of another entity.
-
B.
hasAssociatedCity
Indicates that one entity is linked or related to a specific city, typically as its location, base, or primary area of association.
-
C.
hasComponentCity
Indicates that an entity includes or is composed of one or more cities as its constituent parts.
-
D.
hasTargetCity
Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
-
E.
hasEndpointCity
chosen
Indicates that a route, connection, or path terminates at a particular city as one of its endpoints.
- 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_69e7ab3b92cc81908febd90317862647 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 22, 2026, 8:17 a.m.