Triple
T6922667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico national under-17 football team |
E160224
|
entity |
| Predicate | fifaU17WorldCupTitles |
P73681
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Mexico national under-17 football team, fifaU17WorldCupTitles, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fifaU17WorldCupTitles Context triple: [Mexico national under-17 football team, fifaU17WorldCupTitles, 2]
-
A.
fifaU20WWC_titles
Indicates the number of FIFA U-20 Women's World Cup titles an entity has won.
-
B.
FIFAU20WorldCupTitles
Indicates the number of FIFA U-20 World Cup championship titles an entity has won.
-
C.
fifaU20WWCquarterFinalsAppearances
Indicates the number of times an entity has reached the quarter-final stage of the FIFA U-20 Women's World Cup.
-
D.
FIFAU20WorldCupTitleYear
Indicates the year in which an entity won the FIFA U-20 World Cup title.
-
E.
fifaU20WWCappearances
Indicates the number of times an entity has appeared in FIFA U-20 Women's World Cup matches.
- 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_69c6884d350081908d8a970e4d40ad78 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9fd159c819092a69d1a24e22dd5 |
completed | March 27, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bb577c81908ee8b415b4281f3d |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d98625c88190a37fdf6d95d7fcbd |
completed | March 27, 2026, 7:24 p.m. |
Created at: March 27, 2026, 2:26 p.m.