Triple
T1714513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Stand |
E37259
|
entity |
| Predicate | antagonistGroup |
P17627
|
FINISHED |
| Object | Las Vegas followers of Randall Flagg |
—
|
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: Las Vegas followers of Randall Flagg | Statement: [The Stand, antagonistGroup, Las Vegas followers of Randall Flagg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antagonistGroup Context triple: [The Stand, antagonistGroup, Las Vegas followers of Randall Flagg]
-
A.
hasAntagonistGroup
chosen
Indicates that an entity is opposed or challenged by a specific group acting as its antagonist.
-
B.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
C.
archenemyOf
Indicates a relationship in which one entity is the principal or most important enemy of another, often characterized by deep, ongoing opposition or rivalry.
-
D.
antagonistOccupation
Indicates the role, job, or professional activity that the antagonist character performs.
-
E.
hasProtagonistGroup
Indicates that a narrative work features a central group of characters who collectively serve as the main protagonists.
- 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab7521878c8190b9e7739b8c3fc705 |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61bd46d48190915500d75a9d8e94 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.