Triple
T27166188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pathaan |
E682785
|
entity |
| Predicate | hasAntagonistOrganization |
P17627
|
FINISHED |
| Object | Outfit X |
—
|
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: Outfit X | Statement: [Pathaan, hasAntagonistOrganization, Outfit X]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAntagonistOrganization Context triple: [Pathaan, hasAntagonistOrganization, Outfit X]
-
A.
enemyOfOrganization
Indicates a hostile or adversarial relationship in which an entity opposes, threatens, or acts against an organization.
-
B.
hasAntagonistGroup
chosen
Indicates that an entity is opposed or challenged by a specific group acting as its antagonist.
-
C.
usedByAntagonistOrganization
Indicates that something (such as an object, resource, method, or location) is employed or exploited by an antagonist organization for its purposes.
-
D.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
-
E.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
- 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_69eefacf6e788190a75a64399d9e3109 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6a8df16a88190a23820e64a3b1f92 |
completed | May 3, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 27, 2026, 9:21 a.m.