Triple

T3035968
Position Surface form Disambiguated ID Type / Status
Subject The Lamb E83008 entity
Predicate nearbyIsland P2064 FINISHED
Object Fidra E12804 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: Fidra | Statement: [The Lamb, nearbyIsland, Fidra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fidra
Context triple: [The Lamb, nearbyIsland, Fidra]
  • A. Fidra chosen
    Fidra is a small uninhabited island off the coast of East Lothian, Scotland, known for its lighthouse, seabird colonies, and as an inspiration for Robert Louis Stevenson.
  • B. Freirina
    Freirina is a small town and commune in northern Chile known for its agricultural activity and historic architecture within the Atacama Region.
  • C. Chersina
    Chersina is a genus of tortoises in the family Testudinidae, best known for the South African species Chersina angulata, commonly called the angulate tortoise.
  • D. Sulmo
    Sulmo is an ancient town in central Italy, historically known as the birthplace of the Roman poet Ovid.
  • E. Velda
    Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
  • 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_69ad8b2298908190a7cb4e9bdbf064d0 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9b2bb60c8190b1721f832f2581a1 completed March 8, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f86cfcac81908122f1afd79ce29a completed March 11, 2026, 11:19 p.m.
Created at: March 8, 2026, 3:01 p.m.