Triple
T6562660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Education |
E153821
|
entity |
| Predicate | associatedWithCityType |
P46659
|
FINISHED |
| Object | university town |
—
|
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: university town | Statement: [City of Education, associatedWithCityType, university town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCityType Context triple: [City of Education, associatedWithCityType, university town]
-
A.
hasAssociatedCity
Indicates that one entity is linked or related to a specific city, typically as its location, base, or primary area of association.
-
B.
associatedWithCityNicknameType
Indicates a relationship where a city is linked to a specific type or category of nickname it is known by.
-
C.
connectsTypeOfCity
chosen
Indicates a relationship where one entity is linked to another as a specific type or category of city.
-
D.
cityAssociatedWith
Indicates that there is a notable connection or relationship between a city and another entity, such as relevance, involvement, or contextual association.
-
E.
associatedWithCityFoundation
Indicates a relationship where an entity is connected to, involved in, or relevant to the founding or establishment of a particular city.
- 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_69c6880cb35881909b763eb0125236b9 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6c1b15d3481908ae66e3d7564b352 |
completed | March 27, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69c6acf6d4148190914b19e9affd8c76 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:52 p.m.