Triple
T12163543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santos FC |
E289771
|
entity |
| Predicate | stateLeagueTitles |
P58424
|
FINISHED |
| Object | multiple Campeonato Paulista titles |
—
|
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: multiple Campeonato Paulista titles | Statement: [Santos FC, stateLeagueTitles, multiple Campeonato Paulista titles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stateLeagueTitles Context triple: [Santos FC, stateLeagueTitles, multiple Campeonato Paulista titles]
-
A.
numberOfLeagueTitles
Indicates the total count of league championship titles that an entity has won.
-
B.
team2LeagueTitlesContext
chosen
Indicates that the second team has won league titles within a specified contextual scope (such as a particular time period, competition, or condition).
-
C.
team2LeagueTitles
Indicates that a given team has won a specified number of league titles.
-
D.
mostTitlesTeamTitles
Indicates that the referenced team holds the highest number of titles compared to all other teams in the specified context.
-
E.
team1LeagueTitles
Indicates the number of league titles that the first team has won.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d7109481908bf5fe512bba3c89 |
completed | April 10, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69d9150c18148190bf8152189c0e5fca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.