Triple

T3668443
Position Surface form Disambiguated ID Type / Status
Subject Larkana E77818 entity
Predicate alternateName P39 FINISHED
Object Larkano E77818 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: Larkano | Statement: [Larkana, alternateName, Larkano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Larkano
Context triple: [Larkana, alternateName, Larkano]
  • A. Lapseki
    Lapseki is a town and district in Çanakkale Province in northwestern Turkey, situated on the Asian shore of the Dardanelles Strait.
  • B. Payerne
    Payerne is a historic town and municipality in the canton of Vaud, Switzerland, known for its medieval abbey and regional agricultural significance.
  • C. Larkana chosen
    Larkana is a major city in Pakistan known for its historical significance, including proximity to the ancient Indus Valley site of Mohenjo-daro and its association with the Bhutto political family.
  • D. Arrifes
    Arrifes is a civil parish in the municipality of Ponta Delgada on São Miguel Island in Portugal’s Azores archipelago.
  • E. Mora
    Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
  • 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_69ad85e083008190b2e1b7085fe500bd completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc42997d88190bc765559bd7645fc completed March 8, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4884e36108190a19887e81921fe32 completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:25 p.m.