Triple
T37032166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A-10 |
E916524
|
entity |
| Predicate | associatedWithUniversityArea |
P126227
|
FINISHED |
| Object | Politechnika Warszawska 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: Politechnika Warszawska vicinity | Statement: [A-10, associatedWithUniversityArea, Politechnika Warszawska vicinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithUniversityArea Context triple: [A-10, associatedWithUniversityArea, Politechnika Warszawska vicinity]
-
A.
hasUniversityArea
chosen
Indicates that a specified area or region is designated as the university area associated with a given entity.
-
B.
associatedWithInstitution
Indicates that an entity has a formal or recognized connection or affiliation with an institution.
-
C.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another entity.
-
D.
associatedInstitution
Indicates that an entity has a formal connection or affiliation with a particular institution.
-
E.
hasUniversityCampusArea
Indicates the total physical area occupied by a university’s campus.
- 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_69f76e92c7648190bcfa277f64c71a21 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:14 p.m.