Triple
T5278452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanos family |
E119430
|
entity |
| Predicate | sportsSector |
P24884
|
FINISHED |
| Object | American football |
—
|
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: American football | Statement: [Spanos family, sportsSector, American football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsSector Context triple: [Spanos family, sportsSector, American football]
-
A.
sport
Indicates that an entity participates in, is associated with, or is characterized by a particular athletic activity or game.
-
B.
sportsCategory
Indicates that one entity is classified as a type or category within the domain of sports to which the other entity belongs.
-
C.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
-
D.
sportsAndRecreation
chosen
Indicates a relationship where an entity is associated with, involved in, or designated for sports or recreational activities.
-
E.
otherSportIndustry
Indicates a relationship where an entity is involved in, associated with, or belongs to a sports-related industry other than the primary or specified one.
- 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_69bd446d05a8819092ad333a3f9c8d5c |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8c9c72b08190947b6b955ac1bb5a |
completed | March 20, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69bd844a56b48190ad743c42246e02dd |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:51 p.m.