Triple
T6218819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oregon State Beavers women’s cross country |
E139057
|
entity |
| Predicate | distanceDiscipline |
P27047
|
FINISHED |
| Object | long-distance running |
—
|
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: long-distance running | Statement: [Oregon State Beavers women’s cross country, distanceDiscipline, long-distance running]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceDiscipline Context triple: [Oregon State Beavers women’s cross country, distanceDiscipline, long-distance running]
-
A.
distance
Indicates the spatial separation or length between two points, objects, or locations.
-
B.
raceDistanceType
chosen
Indicates the specific type or category of distance over which a race is conducted.
-
C.
typeDiscipline
Indicates that an entity is associated with, categorized under, or characterized by a particular discipline or field of study.
-
D.
distanceCategory
Indicates the qualitative classification of how far apart two entities are from each other (e.g., near, medium, far).
-
E.
distancedFrom
Indicates that one entity is physically or metaphorically kept at a certain distance or separation from another 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_69c008aecb0c81909984b48f733ce8ae |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062a481908190a1418d9fcfaf8137 |
completed | March 22, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69c055ffdf54819086d987d646e44ff5 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:21 p.m.