Triple
T30383251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weekly Young Jump |
E772882
|
entity |
| Predicate | intendedGenderDemographic |
P83194
|
FINISHED |
| Object | male |
—
|
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 | Statement: [Weekly Young Jump, intendedGenderDemographic, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedGenderDemographic Context triple: [Weekly Young Jump, intendedGenderDemographic, male]
-
A.
genderTarget
chosen
Indicates that an action, message, or effect is specifically directed toward entities of a particular gender.
-
B.
genderCategoryIncludes
Indicates that a given gender category encompasses or contains the specified gender identity or subgroup.
-
C.
genderDepicted
Indicates that the relationship specifies the gender of the entity as it is represented or portrayed in some context.
-
D.
usedByGender
Indicates that something is utilized, applied, or engaged in by entities of a specified gender.
-
E.
sponsoredGender
Indicates that one entity provides financial or material sponsorship specifically related to the gender of another entity.
- 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_69f2248e3444819081b05712dc6873de |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: April 29, 2026, 8:01 p.m.