Triple

T23035128
Position Surface form Disambiguated ID Type / Status
Subject Prince Muhammad Azam E573573 entity
Predicate givenName P17 FINISHED
Object Muhammad Azam 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: Muhammad Azam | Statement: [Prince Muhammad Azam, givenName, Muhammad Azam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muhammad Azam
Context triple: [Prince Muhammad Azam, givenName, Muhammad Azam]
  • A. Muhammad Azam chosen
    Muhammad Azam, better known as Azam Shah, was a Mughal prince who briefly ruled as emperor of the Mughal Empire in the early 18th century.
  • B. Zafar Iqbal
    Zafar Iqbal is an Islamist militant figure best known as one of the founders of the Pakistan-based extremist organization Lashkar-e-Taiba.
  • C. Abdullah Azam Khan
    Abdullah Azam Khan is an Indian politician from Uttar Pradesh, known as the son of senior Samajwadi Party leader Azam Khan and for serving as a member of the state legislative assembly.
  • D. Zahid Ali Khan
    Zahid Ali Khan was a prominent ruler associated with the Wallajah dynasty, known for his role in the political and administrative affairs of the Carnatic region in South India.
  • E. Abid Ali
    Abid Ali is an Indian film producer best known for his work on the landmark 1973 partition drama "Garm Hava."
  • 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.