Triple
T7251122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico national under-20 football team |
E157602
|
entity |
| Predicate | bestResultFIFA U-20 World CupYear |
P75563
|
FINISHED |
| Object | 2011 |
—
|
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: 2011 | Statement: [Mexico national under-20 football team, bestResultFIFA U-20 World CupYear, 2011]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestResultFIFA U-20 World CupYear Context triple: [Mexico national under-20 football team, bestResultFIFA U-20 World CupYear, 2011]
-
A.
fifaU20WWC_bestResult
Indicates the best performance or highest stage a team has achieved in the FIFA U-20 Women's World Cup tournament.
-
B.
bestResultFifaU17WWCYear
Indicates the year in which an entity achieved its best performance or result at the FIFA U-17 Women's World Cup.
-
C.
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.
-
D.
fifaU20WWC_titleYear
Indicates the specific year in which a team or entity won the FIFA U-20 Women's World Cup title.
-
E.
fifaU20WWC_runnersUpYear
Indicates the year in which a team finished as runners-up in the FIFA U-20 Women's World Cup.
- F. None of above. chosen
Provenance (4 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_69c6882d81d4819085f7ff862951ee4f |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea791fec8190aee56ab4503770be |
completed | March 27, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69c6e7666ffc81908bf643d8257e6337 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6e889854481908c765ce2107f2d3a |
completed | March 27, 2026, 8:28 p.m. |
Created at: March 27, 2026, 2:56 p.m.