Triple
T15536199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Mega-Kaiju in Tokyo |
E370351
|
entity |
| Predicate | hasAntagonistForm |
P119074
|
FINISHED |
| Object | combined Kaiju form |
—
|
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: combined Kaiju form | Statement: [Battle of Mega-Kaiju in Tokyo, hasAntagonistForm, combined Kaiju form]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAntagonistForm Context triple: [Battle of Mega-Kaiju in Tokyo, hasAntagonistForm, combined Kaiju form]
-
A.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
-
B.
hasAntagonistGroup
Indicates that an entity is opposed or challenged by a specific group acting as its antagonist.
-
C.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
D.
antagonistStatus
Indicates that an entity holds an opposing or adversarial role, often acting as the main source of conflict relative to another entity or objective.
-
E.
antagonistInvolved
Indicates that an antagonist participates in, influences, or is otherwise actively involved in the referenced event or situation.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0442e327c8190b4b879c8a3cd38e3 |
completed | April 16, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69deda7a95c48190bbe29fadcf17191a |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f05f708190850f1d8782e132b0 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:06 a.m.