Triple

T20853693
Position Surface form Disambiguated ID Type / Status
Subject Siege of Larissa (1083) E513425 entity
Predicate location P40 FINISHED
Object Larissa NE NERFINISHED

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: Larissa | Statement: [Siege of Larissa (1083), location, Larissa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Larissa
Context triple: [Siege of Larissa (1083), location, Larissa]
  • A. Larissa chosen
    Larissa is a major city in central Greece known as an important agricultural, commercial, and transportation hub of the Thessaly region.
  • B. Larissa
    Larissa is one of Neptune’s small, irregularly shaped inner moons, discovered in 1981 and composed primarily of dark, icy material.
  • C. Larisa
    Larisa was an ancient Greek city located in the region of Aeolis in western Asia Minor.
  • D. Larisa
    Larisa is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
  • E. Dymitria
    Dymitria is an alternative name for the Dymitriads, a religious celebration or festival associated with Saint Demetrius in Christian tradition.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4f5b01081909452f654d2fc3f50 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c3a6015081909f604a88d04b36ea completed April 21, 2026, 12:24 a.m.
Created at: April 16, 2026, 12:44 p.m.