Triple

T618006
Position Surface form Disambiguated ID Type / Status
Subject British Sind E14447 entity
Predicate majorCity P316 FINISHED
Object Hyderabad, Sindh E30596 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: Hyderabad, Sindh | Statement: [British Sind, majorCity, Hyderabad, Sindh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hyderabad, Sindh
Context triple: [British Sind, majorCity, Hyderabad, Sindh]
  • A. Hyderabad, Sindh chosen
    Hyderabad, Sindh is a major city in southeastern Pakistan known for its historical role as a regional capital and its rich Sindhi cultural and architectural heritage.
  • B. Sukkur
    Sukkur is a major city in Pakistan known for its strategic location on the Indus River and its role as an important commercial and cultural center in northern Sindh.
  • C. Lahore
    Lahore is a major cultural, historical, and economic center of Pakistan, known for its rich Mughal heritage, educational institutions, and role in the region’s political history.
  • D. Peshawar
    Peshawar is one of Pakistan’s oldest and largest cities, a historic cultural and economic hub located near the Khyber Pass in the country’s northwest.
  • E. Nawabshah
    Nawabshah is a major city in Pakistan known as an important commercial and agricultural center in the Sindh province.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e2418c881908552d2c4a5006e97 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a58a6d19248190a5a57930153a208f completed March 2, 2026, 1:02 p.m.
Created at: March 1, 2026, 7:35 p.m.