Triple

T4294110
Position Surface form Disambiguated ID Type / Status
Subject Outremer E99666 entity
Predicate hasPart P35 FINISHED
Object County of Edessa E46023 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: County of Edessa | Statement: [Outremer, hasPart, County of Edessa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: County of Edessa
Context triple: [Outremer, hasPart, County of Edessa]
  • A. Edessa chosen
    Edessa was an ancient city in Upper Mesopotamia, renowned as a major early center of Syriac Christianity and culture.
  • B. Edessa
    Edessa is a historic city in northern Greece renowned for its picturesque waterfalls and ancient heritage.
  • C. EDESSA
    EDESSA is the company responsible for managing and operating Estadio Cuscatlán, one of the largest and most important football stadiums in El Salvador.
  • D. Osroene
    Osroene was an ancient kingdom and later Roman province in Upper Mesopotamia, centered on the city of Edessa and known for its early Christian heritage.
  • E. County of Tripoli
    The County of Tripoli was a Crusader state established along the Levantine coast in the early 12th century, centered on the city of Tripoli and ruled largely by Frankish nobility.
  • 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_69b3455175088190aa79c6e03b86647e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35083f87c8190a3d3b323e76ab575 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c73d47448190a844bc13eae84a54 completed March 14, 2026, 8:38 p.m.
Created at: March 12, 2026, 11:08 p.m.