Triple
T9355529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miracle on Ice (1981 TV film) |
E225128
|
entity |
| Predicate | sportPortrayed |
P57674
|
FINISHED |
| Object | ice hockey |
—
|
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: ice hockey | Statement: [Miracle on Ice (1981 TV film), sportPortrayed, ice hockey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportPortrayed Context triple: [Miracle on Ice (1981 TV film), sportPortrayed, ice hockey]
-
A.
portraysSport
chosen
Indicates that one entity visually or narratively represents or depicts a particular sport.
-
B.
sportsModel
Indicates a relationship where an entity is a sports-oriented model or variant of another entity (such as a product, design, or system) optimized or styled for sporting use.
-
C.
sportFocus
Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
-
D.
popularSport
Indicates that a sport is widely liked, followed, or played by many people within a certain group or region.
-
E.
sponsorSport
Indicates that one entity financially or materially supports a sport or sporting activity, typically in exchange for promotion or association.
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f99205c8190a5ad95926ef25497 |
completed | April 1, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:42 p.m.