Triple
T28281552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Team Venture |
E713162
|
entity |
| Predicate | hasRecurringNemesis |
P183323
|
FINISHED |
| Object | The Monarch |
—
|
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: The Monarch | Statement: [Team Venture, hasRecurringNemesis, The Monarch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecurringNemesis Context triple: [Team Venture, hasRecurringNemesis, The Monarch]
-
A.
recurringEnemyOf
chosen
Indicates that one entity repeatedly serves as an adversary or opponent to another over multiple encounters or events.
-
B.
hasRecurringActor
Indicates that an actor appears repeatedly across multiple instances or episodes within a work or series.
-
C.
hasRecurringNightmareAbout
Indicates that one entity repeatedly experiences disturbing dreams centered on or involving another entity.
-
D.
hasRecurringProtagonists
Indicates that the same main character or set of main characters appears repeatedly across multiple works or installments in a series.
-
E.
isRecurringCharacter
Indicates that an entity appears repeatedly or regularly within a given narrative, series, or context rather than only once.
- 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_69efb52275788190ae5181ccebef18ce |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69ff409ff5548190849c2d50e99bd807 |
completed | May 9, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69ff401a5e188190a72f945e910b4a6c |
completed | May 9, 2026, 2:09 p.m. |
Created at: April 27, 2026, 11:23 p.m.