Triple
T29362498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timarpur |
E744627
|
entity |
| Predicate | hasNearbyInstitutionalArea |
P6776
|
FINISHED |
| Object | Delhi University |
—
|
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 University | Statement: [Timarpur, hasNearbyInstitutionalArea, Delhi University]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyInstitutionalArea Context triple: [Timarpur, hasNearbyInstitutionalArea, Delhi University]
-
A.
hasNearbyInstitution
chosen
Indicates that one entity is located close to or in the immediate vicinity of an institution.
-
B.
hasNearbyInstitutionType
Indicates that an entity has at least one institution of a specified type located in its nearby geographic vicinity.
-
C.
hasNearbyInstitutionCluster
Indicates that an entity is located close to a concentrated group of related institutions (such as schools, hospitals, or research centers).
-
D.
campusProximity
Indicates that one entity is located near, adjacent to, or within a short distance of a campus associated with the other entity.
-
E.
hasNearbyGeographicalArea
Indicates that one geographical area is located in close spatial proximity to another geographical area.
- 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_69f0a79aee588190b490f19d93c6e52d |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fe163a41a0819098403b470e327d29 |
completed | May 8, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fe1358db5c819092570814a37ef5bd |
completed | May 8, 2026, 4:46 p.m. |
Created at: April 28, 2026, 2:19 p.m.