Triple
T5930475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico national football team |
E131923
|
entity |
| Predicate | worldCupBestResultYear |
P24548
|
FINISHED |
| Object | 1970 |
—
|
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: 1970 | Statement: [Mexico national football team, worldCupBestResultYear, 1970]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldCupBestResultYear Context triple: [Mexico national football team, worldCupBestResultYear, 1970]
-
A.
bestWorldCupResultYear
chosen
Indicates the year in which an entity achieved its best (highest) result in a World Cup tournament.
-
B.
worldCupAppearanceYear
Indicates the specific year in which an entity participated in a FIFA World Cup tournament.
-
C.
worldCupRecord
Indicates a relationship that specifies an entity’s performance statistics or achievements in FIFA World Cup competitions.
-
D.
worldCupTitleYear
Indicates the specific year in which an entity won or held a FIFA World Cup title.
-
E.
worldCupHostYear
Indicates the year in which a particular country or location served as the host of the FIFA World Cup tournament.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c033541d108190a34d1fde2fe9dacb |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4 p.m.