Triple

T6932682
Position Surface form Disambiguated ID Type / Status
Subject Pakistan Railways network E160473 entity
Predicate hasCorridor P5520 FINISHED
Object ML-3
ML-3 is one of Pakistan Railways’ main railway corridors, serving as a key route that supports regional connectivity and freight and passenger movement within the country.
 E632800 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: ML-3 | Statement: [Pakistan Railways network, hasCorridor, ML-3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ML-3
Context triple: [Pakistan Railways network, hasCorridor, ML-3]
  • A. ML3
    ML3 is a UK postcode district covering part of Hamilton and surrounding areas in South Lanarkshire, Scotland.
  • B. ML-2
    ML-2 is a major north–south railway corridor in Pakistan that serves as one of the country’s principal main lines parallel to the primary ML-1 route.
  • C. ML-1
    ML-1 is Pakistan Railways’ primary north–south main line, connecting major cities and serving as the backbone of the country’s rail transport system.
  • D. ML10
    ML10 is a postcode district within the ML (Motherwell) postcode area in central Scotland, covering Strathaven and surrounding settlements.
  • E. MLC
    MLC is the upper house of the bicameral legislature of the Indian state of Maharashtra, responsible for reviewing and passing state legislation.
  • 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: ML-3
Triple: [Pakistan Railways network, hasCorridor, ML-3]
Generated description
ML-3 is one of Pakistan Railways’ main railway corridors, serving as a key route that supports regional connectivity and freight and passenger movement within the country.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ML-3
Target entity description: ML-3 is one of Pakistan Railways’ main railway corridors, serving as a key route that supports regional connectivity and freight and passenger movement within the country.
  • A. ML3
    ML3 is a UK postcode district covering part of Hamilton and surrounding areas in South Lanarkshire, Scotland.
  • B. ML-2
    ML-2 is a major north–south railway corridor in Pakistan that serves as one of the country’s principal main lines parallel to the primary ML-1 route.
  • C. ML-1
    ML-1 is Pakistan Railways’ primary north–south main line, connecting major cities and serving as the backbone of the country’s rail transport system.
  • D. ML10
    ML10 is a postcode district within the ML (Motherwell) postcode area in central Scotland, covering Strathaven and surrounding settlements.
  • E. MLC
    MLC is the upper house of the bicameral legislature of the Indian state of Maharashtra, responsible for reviewing and passing state legislation.
  • 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_69c6884e15208190b9e91487eaafcf85 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da3fa7fc8190a03e7132871a9af4 completed March 27, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76182c848819081b973683bdd235f completed March 28, 2026, 5:05 a.m.
NEDg Description generation batch_69c76354b73081908e4f2482bdefb75b completed March 28, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69c763d604148190a3004ab99c79834f completed March 28, 2026, 5:15 a.m.
Created at: March 27, 2026, 2:27 p.m.