Triple
T22676318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honduras national under-17 football team |
E560354
|
entity |
| Predicate | bestFIFAU17WorldCupResultYear |
P73684
|
FINISHED |
| Object | 2013 |
—
|
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: 2013 | Statement: [Honduras national under-17 football team, bestFIFAU17WorldCupResultYear, 2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestFIFAU17WorldCupResultYear Context triple: [Honduras national under-17 football team, bestFIFAU17WorldCupResultYear, 2013]
-
A.
bestResultFifaU17WWCYear
Indicates the year in which an entity achieved its best performance or result at the FIFA U-17 Women's World Cup.
-
B.
bestResultFifaU17WWC
Indicates that the object is the best performance or highest achievement an entity has attained in the FIFA U-17 Women's World Cup.
-
C.
fifaU17WorldCupBestResult
chosen
Indicates the best performance or highest finishing position a team has achieved in the FIFA U-17 World Cup tournament.
-
D.
bestResultFifaWWCYear
Indicates the year in which an entity achieved its best result in the FIFA Women’s World Cup.
-
E.
fifaU17WorldCupWinningYear
Indicates the specific year in which a given team won the FIFA U-17 World Cup.
- 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1785ca1e08190af1a6cdb51ca4fce |
completed | April 29, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:11 p.m.