Triple
T26900123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bachelorette |
E678002
|
entity |
| Predicate | contestantGender |
P166271
|
FINISHED |
| Object | primarily male 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: primarily male contestants | Statement: [The Bachelorette, contestantGender, primarily male contestants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contestantGender Context triple: [The Bachelorette, contestantGender, primarily male contestants]
-
A.
winnerGender
Indicates the gender of the entity that is the winner in a given event or competition.
-
B.
genderOfCompetitors
chosen
Indicates the gender category or composition of the participants involved in a competition or competitive event.
-
C.
hasPerformerGender
Indicates that an action, event, or performance is associated with the gender of the performer who carries it out.
-
D.
bearerGender
Indicates the gender associated with the bearer in the relationship or context.
-
E.
featuredGender
Indicates that a particular gender is highlighted, emphasized, or given primary focus in a given context or presentation.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f676c440708190a4b9974e95d2291a |
completed | May 2, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f675fd59608190b246383435e68fce |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 27, 2026, 5:50 a.m.