Triple
T22808656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince William Campus |
E564607
|
entity |
| Predicate | publicUniversityCampus |
P149799
|
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: [Prince William Campus, publicUniversityCampus, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicUniversityCampus Context triple: [Prince William Campus, publicUniversityCampus, true]
-
A.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
-
B.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
C.
stateCampus
Indicates that a campus is part of, located within, or administered by a particular state.
-
D.
publicUniversityType
Indicates that an institution is classified as a public university, typically funded and operated by government or state authorities.
-
E.
campus1
Indicates a relationship where an entity is identified as a campus or is located on/associated with a particular campus.
- F. None of above. chosen
Provenance (4 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d5e0b088190ad0b9cc0d5aa1d96 |
completed | April 29, 2026, 3:39 a.m. |
| PD | Predicate disambiguation | batch_69eed2cb30f481909566369f515f6eff |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb5681f88190821129ced752f190 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:32 p.m.