Triple

T23035161
Position Surface form Disambiguated ID Type / Status
Subject Muhammad Azam Shah E573574 entity
Predicate royalTitle P17683 FINISHED
Object Shah 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: Shah | Statement: [Muhammad Azam Shah, royalTitle, Shah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shah
Context triple: [Muhammad Azam Shah, royalTitle, Shah]
  • A. Shah chosen
    Shah is a royal title historically used for monarchs and rulers in Persia (Iran) and other regions of the Islamic world.
  • B. Shah-i Afrid
    Shah-i Afrid was a woman of the Umayyad royal family known primarily as the mother of the caliph al-Walid II.
  • C. King Shahdov
    King Shahdov is the exiled monarch and central figure of Charlie Chaplin’s satirical film "A King in New York," through whom the movie critiques American politics, media, and McCarthy-era paranoia.
  • D. Rahbar
    Rahbar is the title commonly used for the Supreme Leader of Iran, the country's highest political and religious authority.
  • E. Shah Cheragh
    Shah Cheragh is a major Shia Muslim pilgrimage site and mausoleum in Shiraz, Iran, renowned for its dazzling mirrored interior and religious significance.
  • 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_69e245b911188190bc3d96326c847969 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1850df7fc81909ee522d99d96af0d completed April 29, 2026, 4:11 a.m.
Created at: April 17, 2026, 3:53 p.m.