Triple

T15626158
Position Surface form Disambiguated ID Type / Status
Subject صدر آزاد جموں و کشمیر E375683 entity
Predicate officeLocation P40 FINISHED
Object مظفرآباد E1182248 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: مظفرآباد | Statement: [صدر آزاد جموں و کشمیر, officeLocation, مظفرآباد]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: مظفرآباد
Context triple: [صدر آزاد جموں و کشمیر, officeLocation, مظفرآباد]
  • A. مظفرآباد chosen
    مظفرآباد آزاد جموں و کشمیر کا دارالحکومت اور دریائے نیلم و جہلم کے سنگم پر واقع ایک اہم تاریخی و جغرافیائی شہر ہے۔
  • B. Faisalabad
    Faisalabad is a major industrial city in Pakistan’s Punjab province, known especially for its large textile industry and role as a commercial hub.
  • C. Sargodha
    Sargodha is a major city in central Pakistan known for its air force base and extensive citrus (particularly kinnow) production.
  • D. Bahawalpur
    Bahawalpur is a historic city in southern Punjab, Pakistan, known for its former princely state status, grand palaces, and proximity to the Cholistan Desert.
  • E. Bahawalnagar
    Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9e5e248190ae54cda1fde51efb completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffb59535908190a3d085a5e74b06e8 completed May 9, 2026, 10:30 p.m.
Created at: April 10, 2026, 4:14 a.m.