Triple
T30673497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fantastic Four (1967 TV series) |
E780852
|
entity |
| Predicate | depictsAntagonist |
P42601
|
FINISHED |
| Object | Doctor Doom |
—
|
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: Doctor Doom | Statement: [Fantastic Four (1967 TV series), depictsAntagonist, Doctor Doom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsAntagonist Context triple: [Fantastic Four (1967 TV series), depictsAntagonist, Doctor Doom]
-
A.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
B.
portraysAdversary
chosen
Indicates that one entity depicts or represents another entity as an opponent, enemy, or rival.
-
C.
mainAntagonistPortrayedBy
Indicates that the person is the primary actor who plays the main antagonist character in a work.
-
D.
servesAntagonist
Indicates that one entity performs actions in support of, under the command of, or to the benefit of an antagonist.
-
E.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
- 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_69f224a7fc208190a07d6d3879b31640 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7764ab1fc81909f9348db87bd7692 |
completed | May 3, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f76905d9c88190b1ee810bc9ab644f |
completed | May 3, 2026, 3:25 p.m. |
Created at: April 29, 2026, 8:32 p.m.