Triple
T27702561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AFC Women's Futsal Asian Cup |
E698463
|
entity |
| Predicate | secondEditionHostCountry |
P105348
|
FINISHED |
| Object | Thailand |
—
|
NE NERFINISHED |
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: Thailand | Statement: [AFC Women's Futsal Asian Cup, secondEditionHostCountry, Thailand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondEditionHostCountry Context triple: [AFC Women's Futsal Asian Cup, secondEditionHostCountry, Thailand]
-
A.
secondEditionHostCountries
chosen
Indicates the countries that hosted the second edition of a particular event or series.
-
B.
secondPhaseHostCountry
Indicates that a country serves as the host location for the second phase of a multi-phase event, program, or process.
-
C.
semiFinalHostCountry
Indicates the country that serves as the host location for a semifinal stage of a competition or event.
-
D.
secondBoutCountry
Indicates the country in which the second bout or match takes place.
-
E.
lastHostCountry
Indicates the country that most recently hosted a particular event, activity, or entity.
- 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_69ef590ea74081908f0cd7500d85fa27 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
Created at: April 27, 2026, 2:58 p.m.