Triple
T17875103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allen Americans |
E446931
|
entity |
| Predicate | wonLeagueTitles |
P12322
|
FINISHED |
| Object | multiple |
—
|
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 | Statement: [Allen Americans, wonLeagueTitles, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonLeagueTitles Context triple: [Allen Americans, wonLeagueTitles, multiple]
-
A.
numberOfLeagueTitles
Indicates the total count of league championship titles that an entity has won.
-
B.
wonLeagueTitle
chosen
Indicates that a team or individual finished a competition as champions, securing the league title for that season or tournament.
-
C.
winnerTitleCount
Indicates the number of titles or championships an entity has won.
-
D.
consecutiveLeagueTitles
Indicates that one entity has won league titles in successive seasons without interruption.
-
E.
team2LeagueTitlesContext
Indicates that the second team has won league titles within a specified contextual scope (such as a particular time period, competition, or condition).
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49aa54d1481908c0af8533edd51c4 |
completed | April 19, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:18 a.m.