Triple
T38068208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liga MX Apertura 2012 champions |
E950526
|
entity |
| Predicate | firstTopFlightTitleForClub |
P201788
|
FINISHED |
| Object | Club Tijuana |
E58825
|
NE 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: Club Tijuana | Statement: [Liga MX Apertura 2012 champions, firstTopFlightTitleForClub, Club Tijuana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstTopFlightTitleForClub Context triple: [Liga MX Apertura 2012 champions, firstTopFlightTitleForClub, Club Tijuana]
-
A.
firstUEFATitleForClub
Indicates that the referenced UEFA title is the first one ever won by the specified club.
-
B.
numberOfTitlesOfMostSuccessfulClub
Indicates the total count of titles won by the club that has achieved the highest number of titles among all clubs in the given context.
-
C.
firstSeasonClubName
Indicates the name of the club a person or player was associated with in their first season.
-
D.
mostSuccessfulClub
Indicates that one club holds the highest level of success (e.g., by titles, achievements, or performance) compared to all other clubs in the given context.
-
E.
firstWinningClub
chosen
Indicates the club that was the earliest or first to win a particular competition, title, or event.
- F. None of above.
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_69f76f02a6c48190a94f3c0b3ee90cf2 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a4193b3907881908ff7ba8e3596aff4 |
completed | June 28, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:21 p.m.