Triple
T23474136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carla Overbeck |
E570212
|
entity |
| Predicate | teamNumberOfTitlesWithUSWNT |
P152513
|
FINISHED |
| Object | multiple world and Olympic 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 world and Olympic titles | Statement: [Carla Overbeck, teamNumberOfTitlesWithUSWNT, multiple world and Olympic titles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamNumberOfTitlesWithUSWNT Context triple: [Carla Overbeck, teamNumberOfTitlesWithUSWNT, multiple world and Olympic titles]
-
A.
hadUSWNTPlayers
Indicates that an entity (such as a team or club) has included or been associated with players from the United States Women’s National Team.
-
B.
nationalTeamTitleCount
Indicates the number of titles or championships a national team has won.
-
C.
goalsByMeganRapinoe
Indicates the scoring events (goals) that are attributed to Megan Rapinoe.
-
D.
nationalTeamTitles
Indicates the number of titles or championships an entity has won while representing its national team.
-
E.
FIFAWomen'sWorldCupAllTimeTopScorer
Indicates that the subject holds the record for scoring the most goals in the history of the FIFA Women's World Cup.
- 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_69e245af8a88819084f2704f6d265a92 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a70363488190bcbdedec5c2a945c |
completed | April 29, 2026, 6:36 a.m. |
| PD | Predicate disambiguation | batch_69f0620ac3608190b36916261ea50f54 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 5:59 p.m.