Triple

T15060596
Position Surface form Disambiguated ID Type / Status
Subject Larkana Division E379613 entity
Predicate hasMajorCity P316 FINISHED
Object Jacobabad E677858 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: Jacobabad | Statement: [Larkana Division, hasMajorCity, Jacobabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jacobabad
Context triple: [Larkana Division, hasMajorCity, Jacobabad]
  • A. Jacobabad chosen
    Jacobabad is a city in Pakistan’s Sindh province known for its extreme heat, often recording some of the highest temperatures in the country and the world.
  • B. Gujba
    Gujba is a local government area and town in northeastern Nigeria, known for its predominantly rural communities and location within Yobe State.
  • C. Katihar
    Katihar is a city in eastern India known as a major railway junction and commercial center in the state of Bihar.
  • D. Bijnor
    Bijnor is a prominent city in the Indian state of Uttar Pradesh, known for its agricultural economy, especially sugarcane cultivation, and its historical and cultural significance in the region.
  • E. Kanyākubja
    Kanyākubja is an ancient North Indian city of great historical and cultural significance, known today as Kannauj.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69dedee6a55c8190b40c4672fb46b79b completed April 15, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea5c612d481909575b76f7aa96c50 completed May 9, 2026, 3:11 a.m.
Created at: April 10, 2026, 3:01 a.m.