Triple

T3159264
Position Surface form Disambiguated ID Type / Status
Subject Persian E66064 entity
Predicate historicalCapital P2536 FINISHED
Object Ctesiphon E134142 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: Ctesiphon | Statement: [Persian, historicalCapital, Ctesiphon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ctesiphon
Context triple: [Persian, historicalCapital, Ctesiphon]
  • A. Ctesiphon chosen
    Ctesiphon was an ancient metropolis on the Tigris River that served for centuries as the principal capital of the Parthian and later Sasanian Persian empires.
  • B. Samarra
    Samarra is an ancient Iraqi city on the Tigris River renowned for its monumental Islamic architecture, especially the spiral minaret of the Great Mosque of Samarra.
  • C. Edessa
    Edessa is a historic city in northern Greece renowned for its picturesque waterfalls and ancient heritage.
  • D. Edessa
    Edessa was an ancient city in Upper Mesopotamia, renowned as a major early center of Syriac Christianity and culture.
  • E. Susa
    Susa was an ancient city in southwestern Iran that served as a major political and administrative center for several empires, including the Achaemenid Persians.
  • 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_69ad85850c1481908a9e9c6242238de2 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada5ed82a08190a1bdcf18ee593c79 completed March 8, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2250a682c8190b01e949f27d6932e completed March 12, 2026, 2:29 a.m.
Created at: March 8, 2026, 3:05 p.m.