Triple
T24286435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sokutai court robes |
E605682
|
entity |
| Predicate | genderedCounterpart |
P17779
|
FINISHED |
| Object | jūnihitoe (for court ladies) |
—
|
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: jūnihitoe (for court ladies) | Statement: [sokutai court robes, genderedCounterpart, jūnihitoe (for court ladies)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderedCounterpart Context triple: [sokutai court robes, genderedCounterpart, jūnihitoe (for court ladies)]
-
A.
genderedFormOf
chosen
Indicates that one term is a gender-specific variant or inflected form corresponding to another, more neutral or differently gendered term.
-
B.
genderNeutralForm
Indicates that one entity is a gender-neutral linguistic form or expression corresponding to another, more gendered form.
-
C.
genderedPluralForm
Indicates that the plural form of a term is specifically marked or inflected to reflect a particular gender.
-
D.
genderImplication
Indicates that one entity’s gender suggests, constrains, or determines the possible or likely gender of another entity.
-
E.
genderSignificance
Indicates the relevance or impact that an entity’s gender has within a particular context, relationship, or interpretation.
- 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f56cdc08190a1e06f67dffd4769 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:08 a.m.