Triple
T35306943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington–Washington State football rivalry |
E1019662
|
entity |
| Predicate | cityOfCampus1 |
P5417
|
FINISHED |
| Object | Seattle, Washington |
—
|
NE NERFINISHED |
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: Seattle, Washington | Statement: [Washington–Washington State football rivalry, cityOfCampus1, Seattle, Washington]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityOfCampus1 Context triple: [Washington–Washington State football rivalry, cityOfCampus1, Seattle, Washington]
-
A.
cityCampus
chosen
Indicates that a campus is located within or associated with a particular city.
-
B.
hasCampusCity
Indicates that an educational institution or campus is located in a particular city.
-
C.
cityCampusServes
Indicates that a city campus provides services, resources, or support to a particular population, area, or institution.
-
D.
cityOfInstitution
Indicates the city in which an institution is located or based.
-
E.
stateCampus
Indicates that a campus is part of, located within, or administered by a particular state.
- 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_69f76de8b4c48190ae504b86185c474c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:03 p.m.