Triple

T18655203
Position Surface form Disambiguated ID Type / Status
Subject Fanari E456044 entity
Predicate formerNameOf P65 FINISHED
Object Mikrolimano NE NERFINISHED

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: Mikrolimano | Statement: [Fanari, formerNameOf, Mikrolimano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mikrolimano
Context triple: [Fanari, formerNameOf, Mikrolimano]
  • A. Mikrolimano chosen
    Mikrolimano is a picturesque small harbor and marina in Piraeus, Greece, known for its waterfront tavernas, seafood restaurants, and vibrant nightlife.
  • B. Limoncarro
    Limoncarro is an important archaeological site in northern Peru associated with the ancient Cupisnique culture.
  • C. Movia
    Movia is a modular, high-capacity metro train platform developed by Bombardier (now Alstom) and used in urban rail systems worldwide.
  • D. Movia
    Movia is a Danish public transport authority responsible for planning and managing bus services in the Greater Copenhagen area and parts of Zealand.
  • E. Certa Cito
    Certa Cito is the Latin motto of the British Army’s Royal Corps of Signals, reflecting their role in providing swift and reliable military communications.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8d38ea1e88190997e9b231190ba6f completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e55084012881909b9dd60565011c86 completed April 19, 2026, 10 p.m.
Created at: April 10, 2026, 11:47 a.m.