Triple

T12674931
Position Surface form Disambiguated ID Type / Status
Subject Colonel John Parry E302780 entity
Predicate usesAlias P23264 FINISHED
Object Jopari E997518 NE 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: Jopari | Statement: [Colonel John Parry, usesAlias, Jopari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jopari
Context triple: [Colonel John Parry, usesAlias, Jopari]
  • A. Jopari chosen
    Jopari is the name used by Colonel John Parry, a key explorer and shamanic figure in Philip Pullman’s "His Dark Materials" series.
  • B. Japeri
    Japeri is a municipality in the state of Rio de Janeiro, Brazil, known for its location in the Baixada Fluminense region and its role as a railway hub.
  • C. Jopara
    Jopara is a mixed language spoken in Paraguay that blends Guaraní and Spanish in everyday communication.
  • D. Surobi
    Surobi is a town and district in eastern Afghanistan, strategically located along the Kabul River and a key site for nearby hydroelectric infrastructure.
  • E. Kipoi
    Kipoi is a traditional stone-built village in the Zagori region of Epirus, northwestern Greece, known for its arched bridges and well-preserved architecture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961af991c8190b6079cb57e593b8f completed April 10, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c7722788190867cc8a27f678b4f completed May 2, 2026, 10:36 p.m.
Created at: April 9, 2026, 5:20 p.m.