Triple

T11675570
Position Surface form Disambiguated ID Type / Status
Subject Mughal Subah of Bihar E277482 entity
Predicate hasCapital P204 FINISHED
Object Azimabad E379530 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: Azimabad | Statement: [Mughal Subah of Bihar, hasCapital, Azimabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Azimabad
Context triple: [Mughal Subah of Bihar, hasCapital, Azimabad]
  • A. Azimabad chosen
    Azimabad is the former Mughal-era name of the Indian city now known as Patna, reflecting its historical significance under imperial rule.
  • B. Mahmudabad
    Mahmudabad is a coastal city in northern Iran, situated along the Caspian Sea in Mazandaran Province and known for its beaches and tourism.
  • C. Wazirabad
    Wazirabad is a city in the Gujranwala District of Punjab, Pakistan, known for its cutlery industry and strategic location near the Chenab River.
  • D. Shamshabad
    Shamshabad is a suburban area near Hyderabad in the Indian state of Telangana, known primarily for hosting the Rajiv Gandhi International Airport.
  • E. Shahabad
    Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a44504c48190b519765a83ff9c5e completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef13f12c2481909171a3237064c76d completed April 27, 2026, 7:44 a.m.
Created at: April 8, 2026, 9:40 p.m.