Triple
T11951113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bachelor Australia |
E284424
|
entity |
| Predicate | hasContestantGender |
P39348
|
FINISHED |
| Object | female contestants |
—
|
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: female contestants | Statement: [The Bachelor Australia, hasContestantGender, female contestants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasContestantGender Context triple: [The Bachelor Australia, hasContestantGender, female contestants]
-
A.
hasPerformerGender
Indicates that an action, event, or performance is associated with the gender of the performer who carries it out.
-
B.
hasHostGender
Indicates that an entity has or is associated with a specific gender of its host.
-
C.
hasGenderOfPerson
chosen
Indicates that a person is associated with a specific gender classification.
-
D.
winnerGender
Indicates the gender of the entity that is the winner in a given event or competition.
-
E.
hasGenderVariant
Indicates that one entity is a gender-specific form or variant of another entity.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90364c2608190a3946c9595c71164 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.