Triple
T1440857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rio Grande Rivalry |
E31066
|
entity |
| Predicate | distanceBetweenCampuses |
P9492
|
FINISHED |
| Object | approximately 225 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: approximately 225 miles | Statement: [Rio Grande Rivalry, distanceBetweenCampuses, approximately 225 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceBetweenCampuses Context triple: [Rio Grande Rivalry, distanceBetweenCampuses, approximately 225 miles]
-
A.
distanceFromCampusCenter
Indicates the measured or specified distance between a given location and the central point of the campus.
-
B.
campusDistanceBetweenRivals
chosen
Indicates the physical distance separating the campuses of two rival institutions.
-
C.
numberOfCampuses
Indicates the total count of campuses associated with a given entity.
-
D.
adjacentToCampusOf
Indicates that one entity is located next to or directly bordering the campus area of another entity.
-
E.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5ff8dbc81909eafcfc9f2260a22 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c478f65481909ee716791c663491 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.