Triple
T27938030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Lawrence Gordon |
E700663
|
entity |
| Predicate | realNameOfAntagonist |
P106822
|
FINISHED |
| Object | John Kramer |
—
|
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: John Kramer | Statement: [Dr. Lawrence Gordon, realNameOfAntagonist, John Kramer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realNameOfAntagonist Context triple: [Dr. Lawrence Gordon, realNameOfAntagonist, John Kramer]
-
A.
mainAntagonistPortrayedBy
Indicates that the person is the primary actor who plays the main antagonist character in a work.
-
B.
supervillainName
chosen
Indicates that an entity is known by a particular supervillain name or alias.
-
C.
leadAntagonistCharacter
Indicates that one character serves as the primary opposing or villainous force in relation to another entity in the narrative.
-
D.
fullyIntroducedAsAntagonistIn
Indicates that an entity is completely and explicitly presented in a work as an antagonist within the specified context or narrative.
-
E.
characterFullName
Indicates that the predicate specifies the complete, formal name of a character.
- 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_69ef6a5028108190a14696d9821dde49 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f63b317e048190963989b732b25b91 |
completed | May 2, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69f6370ea79c81909b761821ee0fa698 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 7:15 p.m.