Triple

T1197863
Position Surface form Disambiguated ID Type / Status
Subject Indian Police Service E25708 entity
Predicate trainingLocation P40 FINISHED
Object Hyderabad E13440 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 | Statement: [Indian Police Service, trainingLocation, Hyderabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hyderabad
Context triple: [Indian Police Service, trainingLocation, Hyderabad]
  • A. Hyderabad chosen
    Hyderabad is a major city in southern India known for its historic Charminar monument, rich Hyderabadi cuisine, and growing technology industry.
  • B. Hyderabad
    Hyderabad is a major city in the Sindh province of Pakistan, known for its historical significance, vibrant culture, and role as an important commercial and industrial center.
  • C. Vijayawada
    Vijayawada is a major commercial and cultural city in the Indian state of Andhra Pradesh, known as a key transportation hub and an important center for trade, education, and politics in the region.
  • D. Bengaluru
    Bengaluru is a major Indian metropolis known as the country’s leading technology and innovation hub, often called the “Silicon Valley of India.”
  • E. Aurangabad
    Aurangabad is a historic city in the Indian state of Maharashtra, known for its rich cultural heritage and proximity to UNESCO World Heritage Sites like the Ajanta and Ellora Caves.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd9c013c8190822d44d465d60fdb completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde099eb88190ac354f3b4efb0965 completed March 8, 2026, 2:25 a.m.
Created at: March 1, 2026, 7:46 p.m.