Triple
T13537782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betsy Hassett |
E323304
|
entity |
| Predicate | hasPlayedInTournamentType |
P10753
|
FINISHED |
| Object | FIFA women's international tournaments |
—
|
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: FIFA women's international tournaments | Statement: [Betsy Hassett, hasPlayedInTournamentType, FIFA women's international tournaments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlayedInTournamentType Context triple: [Betsy Hassett, hasPlayedInTournamentType, FIFA women's international tournaments]
-
A.
playedInTournament
chosen
Indicates that an entity participated as a competitor or player in a specific tournament.
-
B.
hasTournamentRecord
Indicates that an entity possesses a documented performance or results record in a specific tournament or set of tournaments.
-
C.
hasTournament
Indicates that an entity organizes, hosts, or is associated with a specific tournament.
-
D.
scoredInTournament
Indicates that an entity achieved a score or points during a particular tournament.
-
E.
qualifiedForTournament
Indicates that an entity meets the necessary criteria or requirements to participate in a particular tournament.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafbe39948190808062d4eff91841 |
completed | April 12, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69dbae1046c48190b4ee98c6c9cb9d85 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:45 p.m.