Triple

T3801872
Position Surface form Disambiguated ID Type / Status
Subject Pella regional unit E91706 entity
Predicate capital P234 FINISHED
Object Edessa E105315 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: Edessa | Statement: [Pella regional unit, capital, Edessa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edessa
Context triple: [Pella regional unit, capital, Edessa]
  • A. Edessa chosen
    Edessa is a historic city in northern Greece renowned for its picturesque waterfalls and ancient heritage.
  • B. Edessa
    Edessa was an ancient city in Upper Mesopotamia, renowned as a major early center of Syriac Christianity and culture.
  • C. Hierapolis
    Hierapolis was an ancient Greco-Roman city in Phrygia (modern-day Turkey), known for its hot springs and as an early center of Christianity.
  • D. Turkmenabat
    Turkmenabat is one of the largest cities in Turkmenistan, serving as an important industrial, transport, and cultural center in the country’s east near the border with Uzbekistan.
  • E. Panticapaeum
    Panticapaeum was an important ancient Greek city and trading center on the Cimmerian Bosporus, located where the modern city of Kerch in Crimea now stands.
  • 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_69aed96354f48190a768966d6bd19b04 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee7b998c08190b252178cd7436951 completed March 9, 2026, 3:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f066e30481909e5baa630f3539e4 completed March 14, 2026, 5:21 a.m.
Created at: March 9, 2026, 3:15 p.m.