Triple
T31954632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Act 1, Scene 1 of Othello |
E815869
|
entity |
| Predicate | establishesCharacter |
P182425
|
FINISHED |
| Object | Iago as villain |
—
|
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: Iago as villain | Statement: [Act 1, Scene 1 of Othello, establishesCharacter, Iago as villain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: establishesCharacter Context triple: [Act 1, Scene 1 of Othello, establishesCharacter, Iago as villain]
-
A.
characterSetting
Indicates that a character is associated with, appears in, or is situated within a particular setting or environment.
-
B.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
C.
exampleCharacter
Indicates that one entity is an illustrative or sample character associated with another entity, typically used for demonstration or example purposes.
-
D.
publishesCharacter
Indicates that an entity (such as a publisher or platform) makes a character publicly available or officially releases that character.
-
E.
introducesFictionalCharacter
Indicates that one entity is responsible for first presenting or bringing a fictional character into a narrative work or story.
- 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_69f348f4ec708190abbb2a7c3ed58844 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f78d7211a48190bfb59c406f0bf12f |
completed | May 3, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78c6014e08190864785a4fe3e8e73 |
completed | May 3, 2026, 5:56 p.m. |
Created at: May 1, 2026, 12:08 a.m.