Triple
T1210309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States women's national under-20 soccer team |
E25983
|
entity |
| Predicate | fifaU20WWC_runnersUpYear |
P24686
|
FINISHED |
| Object | 2006 |
—
|
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: 2006 | Statement: [United States women's national under-20 soccer team, fifaU20WWC_runnersUpYear, 2006]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fifaU20WWC_runnersUpYear Context triple: [United States women's national under-20 soccer team, fifaU20WWC_runnersUpYear, 2006]
-
A.
UEFACupRunnersUp
Indicates that an entity finished as the runner-up (losing finalist) in a UEFA Cup competition.
-
B.
FIFAWorldCupParticipation
Indicates that an entity has taken part in at least one edition of the FIFA World Cup tournament.
-
C.
WorldCupSemiFinalAppearances
Indicates the number of times an entity has reached the semi-final stage of a FIFA World Cup tournament.
-
D.
wonConfederationsCup
Indicates that the subject has won the FIFA Confederations Cup tournament.
-
E.
UEFAChampionsLeagueRunnersUp
Indicates that an entity finished in second place (as the losing finalist) in a given season of the UEFA Champions League.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bde4670481908c16a3a8c1a54aad |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6078088190ba0221ae3368416c |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bbf83584819088c69366f58586cc |
completed | March 1, 2026, 10:21 p.m. |
Created at: March 1, 2026, 7:46 p.m.