Triple

T10322251
Position Surface form Disambiguated ID Type / Status
Subject Maragha observatory E242163 entity
Predicate locatedIn P40 FINISHED
Object Maragheh E243700 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: Maragheh | Statement: [Maragha observatory, locatedIn, Maragheh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maragheh
Context triple: [Maragha observatory, locatedIn, Maragheh]
  • A. Maragheh chosen
    Maragheh is a historic city in northwestern Iran known for its rich cultural heritage and notable astronomical observatory from the Ilkhanid era.
  • B. Salmas
    Salmas is a historic city in Iran's West Azerbaijan Province, known for its diverse cultural heritage and location in the northwestern part of the country.
  • C. Sultaniyeh
    Sultaniyeh is a historic city in northwestern Iran best known for its UNESCO-listed Ilkhanid-era mausoleum, one of the largest brick domes in the world.
  • D. El Maragha
    El Maragha is a town in Upper Egypt located within the Sohag Governorate along the Nile River.
  • E. Rayy
    Rayy was an important medieval city near present-day Tehran that served as a major political, commercial, and intellectual hub during the Islamic Golden Age.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d6cce38c8190bfa0f2fb53ed0065 completed April 7, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fb5cbaec8190a9773f8d72d51c1a completed April 9, 2026, 7:17 p.m.
Created at: April 6, 2026, 11:50 a.m.