Triple

T15182330
Position Surface form Disambiguated ID Type / Status
Subject Craterus E362775 entity
Predicate spouse P13 FINISHED
Object Phila E743472 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: Phila | Statement: [Craterus, spouse, Phila]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phila
Context triple: [Craterus, spouse, Phila]
  • A. Phila chosen
    Phila was a prominent Macedonian noblewoman and political figure of the early Hellenistic period, known for her influential role in the power struggles following Alexander the Great’s death.
  • B. Filadelfia
    Filadelfia is a small municipality and town located in the Caldas Department of Colombia, known for its coffee-growing economy in the Andean region.
  • C. Filadelfia
    Filadelfia is a town in the Pando Department of northern Bolivia, located in the Amazon rainforest region near the border with Brazil.
  • D. Philadelphia
    Philadelphia is a 1993 American legal drama film that broke ground in mainstream cinema for its portrayal of HIV/AIDS, homophobia, and discrimination in the workplace.
  • E. Philadelphia
    Philadelphia was the ancient Greco-Roman name of the city now known as Amman, the capital of Jordan.
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e006663ad48190986b680001be0e9b completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd2a2eb48190a569847d2f583c61 completed May 9, 2026, 7:07 a.m.
Created at: April 10, 2026, 3:09 a.m.