Triple

T15556818
Position Surface form Disambiguated ID Type / Status
Subject Chonos Archipelago E370890 entity
Predicate hasPart P35 FINISHED
Object Melinka E1155206 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: Melinka | Statement: [Chonos Archipelago, hasPart, Melinka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Melinka
Context triple: [Chonos Archipelago, hasPart, Melinka]
  • A. Melinka chosen
    Melinka is a small coastal town in southern Chile that serves as the main settlement and administrative center of the remote Guaitecas Archipelago.
  • B. Krasny Kut
    Krasny Kut is a small town in southwestern Russia known as an administrative and agricultural center within the Saratov region.
  • C. Zhulebino
    Zhulebino is a station on the Moscow Metro system, serving the residential Zhulebino district in the southeastern part of Moscow.
  • D. Blansko
    Blansko is a small industrial town in the South Moravian Region of the Czech Republic, known as a gateway to the Moravian Karst cave system.
  • E. Kozelets
    Kozelets is an urban-type settlement in northern Ukraine, historically known as a local administrative and trading center.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a97dbfc8190a98cbbac5e71ba88 completed April 16, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff456427988190bddea01f5cb159d9 completed May 9, 2026, 2:32 p.m.
Created at: April 10, 2026, 4:09 a.m.