Triple
T5980805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boston University–Boston College men's ice hockey rivalry |
E133113
|
entity |
| Predicate | cityDistanceBetweenSchools |
P61194
|
FINISHED |
| Object | approximately 4 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 4 miles | Statement: [Boston University–Boston College men's ice hockey rivalry, cityDistanceBetweenSchools, approximately 4 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityDistanceBetweenSchools Context triple: [Boston University–Boston College men's ice hockey rivalry, cityDistanceBetweenSchools, approximately 4 miles]
-
A.
districtHeadquartersDistance
Indicates the distance between a place and its corresponding district headquarters.
-
B.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
C.
distanceBetweenHomeCities
chosen
Indicates the measured spatial distance separating the home cities of two entities.
-
D.
distanceCharacteristic
Indicates a relationship where an entity is described or constrained by some property or measure of distance (e.g., range, spacing, or separation).
-
E.
distanceCategory
Indicates the qualitative classification of how far apart two entities are from each other (e.g., near, medium, far).
- 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_69c0086f45e8819098f73dd16d45ec9d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:04 p.m.