Triple
T11076797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Male Gothic |
E261886
|
entity |
| Predicate | usedAsTermIn |
P16497
|
FINISHED |
| Object | feminist literary criticism |
—
|
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: feminist literary criticism | Statement: [Male Gothic, usedAsTermIn, feminist literary criticism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsTermIn Context triple: [Male Gothic, usedAsTermIn, feminist literary criticism]
-
A.
usedTerm
chosen
Indicates that one entity employed, referenced, or applied a particular term in some context.
-
B.
isUsedAs
Indicates that one entity serves a particular function, role, or purpose as another entity.
-
C.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
-
D.
isFamouslyUsedIn
Indicates that something is widely recognized or well-known for being used in a particular context, work, or situation.
-
E.
termAlsoUsedFor
Indicates that one term is also used to refer to the same or closely related concept as another term.
- 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7994fcbc081908ff8f7321c0c5892 |
completed | April 9, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69d74415403c81909778bcd829e8832e |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.