Triple
T1882865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duchess of Monmouth |
E39890
|
entity |
| Predicate | genderOfTypicalHolder |
P34342
|
FINISHED |
| Object | female |
—
|
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 | Statement: [Duchess of Monmouth, genderOfTypicalHolder, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderOfTypicalHolder Context triple: [Duchess of Monmouth, genderOfTypicalHolder, female]
-
A.
genderRule
Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
-
B.
namedForGender
Indicates that one entity is named in a way that reflects or is derived from a particular gender or gender-related characteristic of another entity.
-
C.
genderUsage
Indicates how a particular gender is applied, referenced, or treated within a given context or system.
-
D.
hasGenderOfRecipients
Indicates the gender category or composition of the recipients involved in a given relationship or action.
-
E.
hasGenderDistinction
Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb4f53f408190ae30e1a12721e7d7 |
completed | March 7, 2026, 5:17 a.m. |
| PD | Predicate disambiguation | batch_69abafe497a88190a1da6af2888b71b4 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb4f3fb9481908b54506dc2836124 |
completed | March 7, 2026, 5:17 a.m. |
Created at: March 4, 2026, 7:34 p.m.