Triple
T37924150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All Passion Spent |
E946043
|
entity |
| Predicate | hasFeministElements |
P192892
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [All Passion Spent, hasFeministElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFeministElements Context triple: [All Passion Spent, hasFeministElements, true]
-
A.
hasGenderRepresentation
Indicates that something includes, reflects, or portrays one or more genders within its content, structure, or composition.
-
B.
femaleHas
Indicates that a specified entity is female or possesses a female gender attribute in relation to another entity or context.
-
C.
attitudeTowardWomen
Indicates the nature or quality of a subject’s views, feelings, or behavioral disposition toward women.
-
D.
hasFemaleCharacter
Indicates that an entity includes or features at least one female character.
-
E.
hasFeminineFormInSomeLanguages
Indicates that the referenced entity has a distinct feminine grammatical or lexical form in at least one language.
- 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_69f76ef3b7248190892fb9706423be7c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
| PDg | Predicate description generation | batch_69fd2cf29f808190856ab1d43a51d5c7 |
completed | May 8, 2026, 12:23 a.m. |
Created at: May 3, 2026, 4:20 p.m.