Triple

T19694422
Position Surface form Disambiguated ID Type / Status
Subject The Third Expedition E472916 entity
Predicate hasHumanCharacterRole P136950 FINISHED
Object expedition captain 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: expedition captain | Statement: [The Third Expedition, hasHumanCharacterRole, expedition captain]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasHumanCharacterRole
Context triple: [The Third Expedition, hasHumanCharacterRole, expedition captain]
  • A. hasHumanCharacters
    Indicates that the subject includes or features characters that are human beings.
  • B. hasPortrayedPersonRole
    Indicates that an entity has performed or held a specific role in portraying a particular person (e.g., in a film, play, or other representation).
  • C. hasRoleCharacteristic
    Indicates that an entity possesses a specific characteristic, quality, or attribute associated with a particular role.
  • D. hasPlayedRole
    Indicates that an entity has performed or portrayed a particular role or character in some context (such as a film, play, or production).
  • E. hasFictionalRole
    Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
  • F. None of above. chosen

Provenance (4 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_69d8e515bef88190bc30781aea50537a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6421385e88190b22b12ab3d851dea completed April 20, 2026, 3:11 p.m.
PD Predicate disambiguation batch_69e53039ea808190a9106a53f564ab92 completed April 19, 2026, 7:42 p.m.
PDg Predicate description generation batch_69e532bbedf081908d801600e2af94a7 completed April 19, 2026, 7:53 p.m.
Created at: April 10, 2026, 1:46 p.m.