Triple
T4749502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Admiral of the Blue |
E105442
|
entity |
| Predicate | genderApplicability |
P29781
|
FINISHED |
| Object | male officers (historical context) |
—
|
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: male officers (historical context) | Statement: [Admiral of the Blue, genderApplicability, male officers (historical context)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderApplicability Context triple: [Admiral of the Blue, genderApplicability, male officers (historical context)]
-
A.
genderUsage
Indicates how a particular gender is applied, referenced, or treated within a given context or system.
-
B.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
-
C.
genderRule
chosen
Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
-
D.
genderDivision
Indicates a relationship where roles, responsibilities, or categories are separated or distinguished based on gender.
-
E.
sexOrGender
Indicates that one entity has a specified biological sex or socially constructed gender identity.
- 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_69bd43f07fa48190954317d01600994a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64c6f5ac81908a62f9c17e77ac86 |
completed | March 20, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69bd6223defc8190823665a6592c1154 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.