Triple
T32192590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Escape Clause |
E822300
|
entity |
| Predicate | devilCharacterName |
P36851
|
FINISHED |
| Object | Cadwallader |
—
|
NE NERFINISHED |
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: Cadwallader | Statement: [Escape Clause, devilCharacterName, Cadwallader]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: devilCharacterName Context triple: [Escape Clause, devilCharacterName, Cadwallader]
-
A.
nicknameOfAntagonist
Indicates that one entity is a nickname or informal name used for an antagonist entity in a work or context.
-
B.
cultCharacter
Indicates that one entity is a character who is venerated, worshipped, or centrally revered within the cult associated with the other entity.
-
C.
characterName
chosen
Indicates that an entity has a specific name used to identify its character.
-
D.
nonHumanCharacter
Indicates that the character involved in the relation is not a human being (e.g., an animal, creature, AI, or other non-human entity).
-
E.
mainAntagonistPortrayedBy
Indicates that the person is the primary actor who plays the main antagonist character in a work.
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bace6c508190a7b25ad1024151b6 |
completed | May 3, 2026, 3:02 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:35 a.m.