Triple

T15676190
Position Surface form Disambiguated ID Type / Status
Subject Count of Lavagna E377449 entity
Predicate associatedWithFactionalPolitics P106973 FINISHED
Object Genoese internal conflicts 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: Genoese internal conflicts | Statement: [Count of Lavagna, associatedWithFactionalPolitics, Genoese internal conflicts]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithFactionalPolitics
Context triple: [Count of Lavagna, associatedWithFactionalPolitics, Genoese internal conflicts]
  • A. usedByPoliticalFaction
    Indicates that something (such as a resource, symbol, strategy, or tool) is employed or utilized by a specific political faction.
  • B. factionAssociated chosen
    Indicates that an entity is connected to, aligned with, or belongs to a particular faction.
  • C. associatedWithPoliticalAlignment
    Indicates a relationship where an entity is connected to, supports, or is characterized by a particular political ideology, party, or alignment.
  • D. associatedPoliticalSystem
    Indicates that there exists a political system with which the subject is formally or conceptually connected.
  • E. hasPoliticalComponent
    Indicates that something includes, involves, or is influenced by political factors, interests, or considerations.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f2e10a4819097eba1ea31e36ac2 completed April 16, 2026, 2:53 a.m.
PD Predicate disambiguation batch_69deda8b36a4819081cb5708fe77ef51 completed April 15, 2026, 12:23 a.m.
Created at: April 10, 2026, 4:16 a.m.