Triple
T27702562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AFC Women's Futsal Asian Cup |
E698463
|
entity |
| Predicate | secondEditionHostCity |
P185627
|
FINISHED |
| Object | Bangkok |
—
|
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: Bangkok | Statement: [AFC Women's Futsal Asian Cup, secondEditionHostCity, Bangkok]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondEditionHostCity Context triple: [AFC Women's Futsal Asian Cup, secondEditionHostCity, Bangkok]
-
A.
secondEditionHostCountries
Indicates the countries that hosted the second edition of a particular event or series.
-
B.
lastHostCity
Indicates that one entity is the most recent city to have hosted the event or activity associated with the other entity.
-
C.
finalHostCity
Indicates the city that ultimately hosts or is selected to host a particular event or competition.
-
D.
homeCityOfRunnerUpTeam
Indicates the city that serves as the home base for the team that finished in second place in a competition or event.
-
E.
inauguralHostCity
Indicates the city that first hosted a particular event, competition, or series.
- 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_69ef590ea74081908f0cd7500d85fa27 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f7c33d59808190b647989a093f3488 |
completed | May 3, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c29cf36481908e472d4dcb5573b9 |
completed | May 3, 2026, 9:48 p.m. |
Created at: April 27, 2026, 2:58 p.m.