Triple
T22335905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USC–Stanford football rivalry |
E552145
|
entity |
| Predicate | distanceBetweenCampusesApprox |
P9492
|
FINISHED |
| Object | ~350 miles |
—
|
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: ~350 miles | Statement: [USC–Stanford football rivalry, distanceBetweenCampusesApprox, ~350 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceBetweenCampusesApprox Context triple: [USC–Stanford football rivalry, distanceBetweenCampusesApprox, ~350 miles]
-
A.
campusDistanceBetweenRivals
chosen
Indicates the physical distance separating the campuses of two rival institutions.
-
B.
distanceFromCampusCenter
Indicates the measured or specified distance between a given location and the central point of the campus.
-
C.
campusProximity
Indicates that one entity is located near, adjacent to, or within a short distance of a campus associated with the other entity.
-
D.
separatesCampusesOf
Indicates that one entity serves as a dividing boundary or barrier between two or more campuses.
-
E.
numberOfCampuses
Indicates the total count of campuses associated with a given entity.
- 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_69e11e494eec81909c4d2d51f69499d9 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1577f2f208190ac6270ac4581fa15 |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e7300c20088190a59e5bf9e70384f3 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:43 p.m.