Triple

T14732876
Position Surface form Disambiguated ID Type / Status
Subject M-9 Motorway E346120 entity
Predicate passesNear P416 FINISHED
Object Nooriabad
Nooriabad is an industrial town in the Jamshoro District of Sindh, Pakistan, known for its manufacturing zones and proximity to Karachi.
E1118220 NE FINISHED

How this triple was built (4 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: Nooriabad | Statement: [M-9 Motorway, passesNear, Nooriabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nooriabad
Context triple: [M-9 Motorway, passesNear, Nooriabad]
  • A. Nasirabad
    Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
  • B. Nasirabad
    Nasirabad is a village in the Lower Hunza region of northern Pakistan, known for its mountainous terrain and proximity to the Karakoram Range.
  • C. Muhammadabad
    Muhammadabad is a town located in the Ghazipur district of the Indian state of Uttar Pradesh.
  • D. Yaseenabad
    Yaseenabad is a residential neighborhood located within the Federal B Area of Karachi, Pakistan.
  • E. Shahabad
    Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nooriabad
Triple: [M-9 Motorway, passesNear, Nooriabad]
Generated description
Nooriabad is an industrial town in the Jamshoro District of Sindh, Pakistan, known for its manufacturing zones and proximity to Karachi.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nooriabad
Target entity description: Nooriabad is an industrial town in the Jamshoro District of Sindh, Pakistan, known for its manufacturing zones and proximity to Karachi.
  • A. Nasirabad
    Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
  • B. Nasirabad
    Nasirabad is a village in the Lower Hunza region of northern Pakistan, known for its mountainous terrain and proximity to the Karakoram Range.
  • C. Muhammadabad
    Muhammadabad is a town located in the Ghazipur district of the Indian state of Uttar Pradesh.
  • D. Yaseenabad
    Yaseenabad is a residential neighborhood located within the Federal B Area of Karachi, Pakistan.
  • E. Shahabad
    Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
  • F. None of above. chosen

Provenance (5 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec72ea9348190817efcdaa973d7f7 completed April 14, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0ce3d1d88190951e88bef88db500 completed May 8, 2026, 4:18 p.m.
NEDg Description generation batch_69fe13d318ac81909d339c4cc5c83070 completed May 8, 2026, 4:48 p.m.
NED2 Entity disambiguation (via description) batch_69fe142e5030819081bfe87d5d7b6581 completed May 8, 2026, 4:49 p.m.
Created at: April 10, 2026, 1:29 a.m.