Triple
T29643003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess of Hesse and by Rhine |
E755913
|
entity |
| Predicate | titleGenderRestriction |
P15554
|
FINISHED |
| Object | female only |
—
|
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 only | Statement: [Princess of Hesse and by Rhine, titleGenderRestriction, female only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleGenderRestriction Context triple: [Princess of Hesse and by Rhine, titleGenderRestriction, female only]
-
A.
genderCategoryIncludes
Indicates that a given gender category encompasses or contains the specified gender identity or subgroup.
-
B.
hasGenderRequirement
chosen
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
C.
governsGender
Indicates that one entity determines or constrains the gender classification or gender-related properties of another entity.
-
D.
hasGenderFormat
Indicates that something is associated with or expressed in a particular gender-related format or representation.
-
E.
hasGenderNeutralEligibility
Indicates that an entity is eligible or applicable in a way that does not depend on or specify a particular gender.
- 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_69f0ef89d2c88190a6d0d5116ccd7cc9 |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: April 28, 2026, 6:48 p.m.