Triple
T21465025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jezebel (play) |
E529571
|
entity |
| Predicate | titleCharacterConsequence |
P92378
|
FINISHED |
| Object | social ostracism |
—
|
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: social ostracism | Statement: [Jezebel (play), titleCharacterConsequence, social ostracism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleCharacterConsequence Context triple: [Jezebel (play), titleCharacterConsequence, social ostracism]
-
A.
titleCharacterState
Indicates the state or condition a character is in within the context of a specific title or work.
-
B.
titleCharacterRelation
chosen
Indicates the relationship between a work’s title and a specific character it references or centers on.
-
C.
titleCharacterNamedAfter
Indicates that a work’s title character is named after, or shares their name with, another specific entity.
-
D.
tormentsCharacter
Indicates that one entity causes ongoing psychological or physical suffering to another character.
-
E.
titleCharacterString
Indicates that one entity is the textual string representing the title associated with 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_69e0c458133481908ae8b41a12c4edec |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9f1b3cc819092c200f09c6f461e |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631df1b38819088d3604854e697b4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:09 p.m.