Triple
T18570507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1997 Asia Cup |
E453860
|
entity |
| Predicate | titleNumberOfChampion |
P100670
|
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: [1997 Asia Cup, titleNumberOfChampion, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleNumberOfChampion Context triple: [1997 Asia Cup, titleNumberOfChampion, 2]
-
A.
totalChampionsCount
Indicates the total number of champions associated with or involved in a given context or entity.
-
B.
titleTotalNumberForChampion
chosen
Indicates the total count of titles that a given champion has achieved.
-
C.
championCityTitleNumber
Indicates the ordinal number of championship titles that a particular city has won or holds in a given competition or league.
-
D.
firstTitleForChampion
Indicates that the associated title is the first championship title ever won by the specified champion.
-
E.
consecutiveTitleNumberForChampion
Indicates that the associated number represents how many titles a champion has won consecutively up to that point.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53b01331c8190bec3aba40358a843 |
completed | April 19, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69e478c16e0c8190b03966aa23c395a6 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:43 a.m.