Triple

T18401353
Position Surface form Disambiguated ID Type / Status
Subject Berkely Mather E450002 entity
Predicate notableWork P4 FINISHED
Object The Road to Lahore — NE NERFINISHED

How this triple was built (3 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: The Road to Lahore | Statement: [Berkely Mather, notableWork, The Road to Lahore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: The Road to Lahore
Context triple: [Berkely Mather, notableWork, The Road to Lahore]
  • A. Roads to Multan
    Roads to Multan are the key transport routes linking the city of Multan with surrounding districts and regions, facilitating regional trade and travel in southern Punjab, Pakistan.
  • B. Le roi de Lahore
    Le roi de Lahore is a five-act French grand opera by Jules Massenet, first performed in 1877 and set in medieval India with themes of love, sacrifice, and reincarnation.
  • C. Train to Pakistan
    Train to Pakistan is a landmark historical novel by Khushwant Singh that portrays the human tragedy and communal violence surrounding the Partition of India in 1947.
  • D. "Demons of the Punjab"
    "Demons of the Punjab" is a 2018 Doctor Who episode set during the Partition of India, blending historical drama with science fiction as the Doctor uncovers the truth behind mysterious alien presences amid human tragedy.
  • E. Khak-e Safid
    Khak-e Safid is a rural settlement in western Afghanistan known primarily as a district center within Farah Province.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: The Road to Lahore
Target entity description: The Road to Lahore is a mid-20th-century adventure novel by British writer Berkely Mather, known for its suspenseful storytelling and exotic settings.
  • A. Roads to Multan
    Roads to Multan are the key transport routes linking the city of Multan with surrounding districts and regions, facilitating regional trade and travel in southern Punjab, Pakistan.
  • B. Le roi de Lahore
    Le roi de Lahore is a five-act French grand opera by Jules Massenet, first performed in 1877 and set in medieval India with themes of love, sacrifice, and reincarnation.
  • C. Train to Pakistan
    Train to Pakistan is a landmark historical novel by Khushwant Singh that portrays the human tragedy and communal violence surrounding the Partition of India in 1947.
  • D. "Demons of the Punjab"
    "Demons of the Punjab" is a 2018 Doctor Who episode set during the Partition of India, blending historical drama with science fiction as the Doctor uncovers the truth behind mysterious alien presences amid human tragedy.
  • E. Khak-e Safid
    Khak-e Safid is a rural settlement in western Afghanistan known primarily as a district center within Farah Province.
  • F. None of above.

Provenance (2 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_69d8b9fab8a8819086a9ddc0871715e0 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e5195185b08190bd3b5471cdc047b0 completed April 19, 2026, 6:05 p.m.
Created at: April 10, 2026, 10:46 a.m.