Triple

T11397993
Position Surface form Disambiguated ID Type / Status
Subject Mario Laserna Pinzón E270029 entity
Predicate familyName P18 FINISHED
Object Laserna E270029 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: Laserna | Statement: [Mario Laserna Pinzón, familyName, Laserna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laserna
Context triple: [Mario Laserna Pinzón, familyName, Laserna]
  • A. Laserna chosen
    Laserna is a Spanish-language surname most notably associated with Colombian intellectual and politician Mario Laserna Pinzón.
  • B. Lasbela
    Lasbela is a coastal district and city in Pakistan’s Balochistan province, known for its strategic location near Karachi and its mix of industrial, agricultural, and fishing activities.
  • C. Kaladar
    Kaladar is a small rural community located within the township of Addington Highlands in eastern Ontario, Canada.
  • D. Khwabgah
    Khwabgah is a historic residential complex within the Mughal imperial city of Fatehpur Sikri, traditionally regarded as the private sleeping quarters of Emperor Akbar.
  • E. Lichmera
    Lichmera is a genus of honeyeaters, small nectar-feeding passerine birds native mainly to Australasia and surrounding regions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aacdbc6c8190af6dc3d5f5d22836 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d80019d3d48190a2f473deb6eae33a completed April 9, 2026, 7:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58cd74280819092f8c420630f4889 completed April 20, 2026, 2:17 a.m.
Created at: April 8, 2026, 9:34 p.m.