Triple
T39130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European polytechnic institutes |
E774
|
entity |
| Predicate | oftenInclude |
P1393
|
FINISHED |
| Object | innovation and entrepreneurship centers |
—
|
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: innovation and entrepreneurship centers | Statement: [European polytechnic institutes, oftenInclude, innovation and entrepreneurship centers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenInclude Context triple: [European polytechnic institutes, oftenInclude, innovation and entrepreneurship centers]
-
A.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
B.
involves
Indicates that an entity participates in, is a part of, or is implicated within a particular event, process, or relationship.
-
C.
allows
Indicates that one entity grants permission, capability, or opportunity for another entity to perform an action or be in a certain state.
-
D.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
E.
meets
Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24b4d5bd08190a3a48eb26e67768c |
completed | Feb. 28, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a24ab6141881908701106aa97e4735 |
completed | Feb. 28, 2026, 1:53 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.