Triple

T38100391
Position Surface form Disambiguated ID Type / Status
Subject Karachi industrial belt E951360 entity
Predicate hasPart P35 FINISHED
Object Bin Qasim Industrial Zone
Bin Qasim Industrial Zone is a major industrial estate in Karachi, Pakistan, hosting a concentration of large-scale manufacturing and export-oriented industries near the Port Qasim area.
E2258119 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: Bin Qasim Industrial Zone | Statement: [Karachi industrial belt, hasPart, Bin Qasim Industrial Zone]
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: Bin Qasim Industrial Zone
Triple: [Karachi industrial belt, hasPart, Bin Qasim Industrial Zone]
Generated description
Bin Qasim Industrial Zone is a major industrial estate in Karachi, Pakistan, hosting a concentration of large-scale manufacturing and export-oriented industries near the Port Qasim area.

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_69f76f04960c8190a83f14ae4c67f5bc completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc45a2a9a08190885c9ece99e1bd18 completed May 7, 2026, 7:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a417119da708190a9e0a516c71fd333 completed June 28, 2026, 7:08 p.m.
NEDg Description generation batch_6a4172291ffc8190a67594e8b2cb42e0 completed June 28, 2026, 7:12 p.m.
NED2 Entity disambiguation (via description) batch_6a4172cc0a288190a82f0f22593f5861 completed June 28, 2026, 7:15 p.m.
Created at: May 3, 2026, 4:21 p.m.