Triple
T36145200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viola (Twelfth Night) |
E1045427
|
entity |
| Predicate | intertextualInfluenceOn |
P18315
|
FINISHED |
| Object | later cross-dressing heroines in drama and fiction |
—
|
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: later cross-dressing heroines in drama and fiction | Statement: [Viola (Twelfth Night), intertextualInfluenceOn, later cross-dressing heroines in drama and fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intertextualInfluenceOn Context triple: [Viola (Twelfth Night), intertextualInfluenceOn, later cross-dressing heroines in drama and fiction]
-
A.
intertextualRelation
Indicates a relationship in which one text references, echoes, or otherwise meaningfully connects to another text.
-
B.
literaryInfluence
chosen
Indicates that one entity has had a significant impact on the style, themes, or development of another entity’s literary work.
-
C.
incorporatesInfluence
Indicates that one entity integrates or absorbs the influence, ideas, or characteristics of another into itself.
-
D.
influenceOf
Indicates that one entity affects, shapes, or alters the state, behavior, or properties of another entity.
-
E.
wereInfluencedBy
Indicates that one entity’s ideas, actions, or characteristics were shaped or affected by 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_69f76e37ace88190a906b107d388f5d1 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
Created at: May 3, 2026, 4:08 p.m.