Triple
T13252343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2015 National Women's Soccer League season |
E315563
|
entity |
| Predicate | totalRegularSeasonMatches |
P8183
|
FINISHED |
| Object | 90 |
—
|
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: 90 | Statement: [2015 National Women's Soccer League season, totalRegularSeasonMatches, 90]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalRegularSeasonMatches Context triple: [2015 National Women's Soccer League season, totalRegularSeasonMatches, 90]
-
A.
totalMatchesPerSeason
chosen
Indicates the total number of matches associated with an entity within a single season.
-
B.
hasRegularSeasonMeetings
Indicates that one entity holds recurring scheduled meetings with another entity during the regular season.
-
C.
regularSeasonGamesPlayed
Indicates the number of games an entity participated in during the regular season of a competition or league.
-
D.
regularSeasonGamesPerTeam
Indicates the number of games each team plays during the regular season.
-
E.
hasRegularSeasonGamesAgainst
Indicates that one team or participant plays scheduled, recurring competitive games against another during the regular season.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f60911081909fa346a054f76c9f |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:24 p.m.