Triple

T16624901
Position Surface form Disambiguated ID Type / Status
Subject Krimzon Guard fortress E403919 entity
Predicate enemyTypePresent P99416 FINISHED
Object Krimzon Guard soldiers 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: Krimzon Guard soldiers | Statement: [Krimzon Guard fortress, enemyTypePresent, Krimzon Guard soldiers]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: enemyTypePresent
Context triple: [Krimzon Guard fortress, enemyTypePresent, Krimzon Guard soldiers]
  • A. enemyType
    Indicates that one entity is classified as an enemy of a specified type or category in relation to another entity.
  • B. enemyForceType chosen
    Indicates that one entity is characterized as a hostile or opposing force of a specified type relative to another entity.
  • C. hasOpposingForceType
    Indicates that one force is characterized as being of a type that opposes or counteracts another force.
  • D. hasCreature
    Indicates that one entity possesses, contains, or is associated with a particular creature.
  • E. enemyCharacterIn
    Indicates that a character is located within or present inside an enemy-controlled area, zone, or context.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37551cd888190becc21deba87980d completed April 18, 2026, 12:13 p.m.
PD Predicate disambiguation batch_69e296ad3f148190af09223dc35b155c completed April 17, 2026, 8:23 p.m.
Created at: April 10, 2026, 5:17 a.m.