Triple
T26038375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thailand national football team |
E647615
|
entity |
| Predicate | affChampionshipTitlesYears |
P160709
|
FINISHED |
| Object | 2000 |
—
|
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: 2000 | Statement: [Thailand national football team, affChampionshipTitlesYears, 2000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affChampionshipTitlesYears Context triple: [Thailand national football team, affChampionshipTitlesYears, 2000]
-
A.
affChampionshipTitles
Indicates that an entity has won or been awarded a specified number of championship titles.
-
B.
worldChampionshipTitleYear
Indicates the specific year in which an entity won a world championship title.
-
C.
championPreviousTitleYear
Indicates the year in which the current champion previously held the same title.
-
D.
championshipEndYear
Indicates the calendar year in which a particular championship or title-holding period concludes.
-
E.
championshipsABAYears
Indicates the years in which entity A won championships associated with or against entity B.
- 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_69e77e8c88f08190858c4c81bd2e1b9a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f60620fb648190826cfb2fdefe4858 |
completed | May 2, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f603b90c94819088d62cb9489e95ff |
completed | May 2, 2026, 2:01 p.m. |
Created at: April 22, 2026, 9:08 a.m.