Triple
T20070511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STU |
E499721
|
entity |
| Predicate | isTechnicalUniversity |
P90781
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [STU, isTechnicalUniversity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTechnicalUniversity Context triple: [STU, isTechnicalUniversity, true]
-
A.
hasTechnicalUniversity
Indicates that a place or organization possesses or hosts a technical university as part of its institutions or infrastructure.
-
B.
isLargestTechnicalUniversityIn
Indicates that a university is the largest technical university within a specified region or group.
-
C.
isResearchUniversity
Indicates that an institution functions primarily as a research-focused university, emphasizing the creation of new knowledge alongside advanced education.
-
D.
hasTechnicalCollege
Indicates that an entity possesses, includes, or is associated with a technical college as part of its structure or offerings.
-
E.
typeOfUniversity
chosen
Indicates the specific category or classification of a university (e.g., public, private, technical, etc.) that an institution belongs to.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643798a4819081fa4e71c74b47bc |
completed | April 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:40 p.m.