Triple
T36292971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Downtown Campus of the University at Buffalo |
E893280
|
entity |
| Predicate | isUrbanHealthSciencesHubFor |
P185107
|
FINISHED |
| Object | University at Buffalo |
—
|
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: University at Buffalo | Statement: [Downtown Campus of the University at Buffalo, isUrbanHealthSciencesHubFor, University at Buffalo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanHealthSciencesHubFor Context triple: [Downtown Campus of the University at Buffalo, isUrbanHealthSciencesHubFor, University at Buffalo]
-
A.
isUrbanHubFor
Indicates that a location functions as a central urban focal point or primary service center for another area or population.
-
B.
isUrbanUniversity
Indicates that a university is located in, or primarily associated with, an urban (city) environment.
-
C.
isUrbanHospital
Indicates that a hospital is located in an urban area or serves an urban population.
-
D.
isUrbanService
Indicates that a service operates within or is specifically intended for an urban area or city environment.
-
E.
hasUrbanInstitution
Indicates that an entity possesses, hosts, or is associated with an institution located in an urban area.
- F. None of above. chosen
Provenance (4 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_69f76e4a61f0819084a2b68dbbb4efc6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb1d6b70819091227bd011734d19 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7ba6c27e081908868a2b50d1d603c |
completed | May 3, 2026, 9:13 p.m. |
Created at: May 3, 2026, 4:09 p.m.