Triple

T6932680
Position Surface form Disambiguated ID Type / Status
Subject Pakistan Railways network E160473 entity
Predicate hasMainCorridor P5520 FINISHED
Object 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.
 E629105 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-1 | Statement: [Pakistan Railways network, hasMainCorridor, ML-1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ML-1
Context triple: [Pakistan Railways network, hasMainCorridor, ML-1]
  • A. ML10
    ML10 is a postcode district within the ML (Motherwell) postcode area in central Scotland, covering Strathaven and surrounding settlements.
  • B. ML3
    ML3 is a UK postcode district covering part of Hamilton and surrounding areas in South Lanarkshire, Scotland.
  • C. MLC
    MLC is the upper house of the bicameral legislature of the Indian state of Maharashtra, responsible for reviewing and passing state legislation.
  • D. MLI
    MLI is the three-letter ISO 3166-1 alpha-3 country code assigned to Mali.
  • E. MLN
    MLN is the IATA airport code for Melilla Airport, which serves the Spanish autonomous city of Melilla on the north coast of Africa.
  • 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-1
Triple: [Pakistan Railways network, hasMainCorridor, ML-1]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ML-1
Target entity description: 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.
  • A. ML10
    ML10 is a postcode district within the ML (Motherwell) postcode area in central Scotland, covering Strathaven and surrounding settlements.
  • B. ML3
    ML3 is a UK postcode district covering part of Hamilton and surrounding areas in South Lanarkshire, Scotland.
  • C. MLC
    MLC is the upper house of the bicameral legislature of the Indian state of Maharashtra, responsible for reviewing and passing state legislation.
  • D. MLI
    MLI is the three-letter ISO 3166-1 alpha-3 country code assigned to Mali.
  • E. MLN
    MLN is the IATA airport code for Melilla Airport, which serves the Spanish autonomous city of Melilla on the north coast of Africa.
  • 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_69c6e1cfd8fc81908efb83c061cb8e4f completed March 27, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7514b0dd8819097a3fa1a38c913f4 completed March 28, 2026, 3:55 a.m.
NEDg Description generation batch_69c75280eaa4819089b5e76a817b1330 completed March 28, 2026, 4:01 a.m.
NED2 Entity disambiguation (via description) batch_69c75306e62c8190ba2f4db741bd1ff9 completed March 28, 2026, 4:03 a.m.
Created at: March 27, 2026, 2:27 p.m.