Triple

T14967385
Position Surface form Disambiguated ID Type / Status
Subject Sann E373224 entity
Predicate hasNearbyCity P350 FINISHED
Object Jamshoro E645219 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: Jamshoro | Statement: [Sann, hasNearbyCity, Jamshoro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jamshoro
Context triple: [Sann, hasNearbyCity, Jamshoro]
  • A. Jamshoro chosen
    Jamshoro is a city in the Sindh province of Pakistan known as an important educational hub, hosting several major universities and research institutions.
  • B. Jauharabad
    Jauharabad is a planned town in Pakistan’s Punjab province, known for its proximity to key industrial and strategic facilities.
  • 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. Hafizabad
    Hafizabad is a prominent city in Pakistan’s Punjab province, known for its rice production and role as an agricultural and commercial center.
  • E. Shujabad
    Shujabad is a city in southern Punjab, Pakistan, known for its agricultural economy and proximity to the regional center of Multan.
  • 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_69d85ccbbcd48190acb56e7cf104d8ad completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6e44cb0819096e09f8026ef8174 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea5aaeda08190846c15562e67c1fb completed May 9, 2026, 3:10 a.m.
Created at: April 10, 2026, 2:48 a.m.