Triple
T16114067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Şehzadebaşı Caddesi |
E390957
|
entity |
| Predicate | hasNearbyEducationBuilding |
P84383
|
FINISHED |
| Object | Istanbul University vicinity |
—
|
LITERAL FINISHED |
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: Istanbul University vicinity | Statement: [Şehzadebaşı Caddesi, hasNearbyEducationBuilding, Istanbul University vicinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyEducationBuilding Context triple: [Şehzadebaşı Caddesi, hasNearbyEducationBuilding, Istanbul University vicinity]
-
A.
hasNearbyInstitution
Indicates that one entity is located close to or in the immediate vicinity of an institution.
-
B.
hasNearbyInstitutionType
chosen
Indicates that an entity has at least one institution of a specified type located in its nearby geographic vicinity.
-
C.
campusProximity
Indicates that one entity is located near, adjacent to, or within a short distance of a campus associated with the other entity.
-
D.
adjacentToCampusOf
Indicates that one entity is located next to or directly bordering the campus area of another entity.
-
E.
educationFacility
Indicates that one entity functions as an institution or place where the other entity receives or provides education or training.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20169ce488190bbc814f23a3b7547 |
completed | April 17, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5 a.m.