Triple
T36963724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clockwork Mansion |
E914371
|
entity |
| Predicate | canSpareAntagonist |
P186812
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Clockwork Mansion, canSpareAntagonist, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canSpareAntagonist Context triple: [Clockwork Mansion, canSpareAntagonist, yes]
-
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.
hasAntagonistForm
Indicates that an entity possesses or takes on a form characterized by opposition, hostility, or antagonistic behavior toward another entity.
-
C.
hasVillain
Indicates that one entity is the villain or primary antagonist associated with another entity.
-
D.
servesAntagonist
Indicates that one entity performs actions in support of, under the command of, or to the benefit of an antagonist.
-
E.
antagonistAlterEgoOf
Indicates that one entity serves as the primary opposing force or enemy of another entity’s alternate identity or secret persona.
- 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_69f76e8c498c8190b2842db80aea8b3b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fa0a7b00948190a257273d9968c5d7 |
completed | May 5, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f9fec9c9488190ae2a349651a02782 |
completed | May 5, 2026, 2:29 p.m. |
| PDg | Predicate description generation | batch_69fa0a799b9081909bfa8293a22c4b00 |
completed | May 5, 2026, 3:19 p.m. |
Created at: May 3, 2026, 4:14 p.m.