Triple
T7043162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Industrial Engineering Department at Boğaziçi University |
E163563
|
entity |
| Predicate | sectorCollaboration |
P26572
|
FINISHED |
| Object | manufacturing industry |
—
|
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: manufacturing industry | Statement: [Industrial Engineering Department at Boğaziçi University, sectorCollaboration, manufacturing industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorCollaboration Context triple: [Industrial Engineering Department at Boğaziçi University, sectorCollaboration, manufacturing industry]
-
A.
collaborationArea
chosen
Indicates the domain, topic, or field in which two or more entities work together or collaborate.
-
B.
collaborationOf
Indicates a relationship in which two or more entities work together jointly toward a shared goal or outcome.
-
C.
collaborationAspect
Indicates a specific characteristic, dimension, or feature of how entities collaborate or work together.
-
D.
collaborationRegion
Indicates the geographic or administrative area within which the collaboration between entities takes place or is defined.
-
E.
sectoralOrganizations
Indicates that there is an organizational relationship specifically structured around a particular sector or industry.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bb602081908bfa6186a1f5a4b4 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:36 p.m.