Triple
T18469776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1996–97 American Basketball League season |
E451265
|
entity |
| Predicate | positionRelativeToWNBA |
P131770
|
FINISHED |
| Object | alternative to the WNBA |
—
|
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: alternative to the WNBA | Statement: [1996–97 American Basketball League season, positionRelativeToWNBA, alternative to the WNBA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionRelativeToWNBA Context triple: [1996–97 American Basketball League season, positionRelativeToWNBA, alternative to the WNBA]
-
A.
WNBAJerseyNumber
Indicates that a specific WNBA player wears or is assigned a particular jersey number.
-
B.
averagePlayerSalaryComparedToWNBA
Indicates how the average salary of a given group of players compares in magnitude to the average salary of WNBA players.
-
C.
WNBAFranchiseDebutYear
Indicates the year in which a WNBA franchise first began play in the league.
-
D.
WNBAteam
Indicates that the subject is a team that competes in the Women’s National Basketball Association (WNBA).
-
E.
numberOfWNBAChampionships
Indicates the count of WNBA championship titles that an entity has won.
- 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5305e349c8190925166bc3dddb320 |
completed | April 19, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69e469d05cf4819099baf1665a9cf18a |
completed | April 19, 2026, 5:36 a.m. |
| PDg | Predicate description generation | batch_69e46d2aa72c8190a40854a7a52081e2 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 11:34 a.m.