Triple

T4917461
Position Surface form Disambiguated ID Type / Status
Subject Letoon E110382 entity
Predicate dedicatedTo P500 FINISHED
Object Leto E19957 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: Leto | Statement: [Letoon, dedicatedTo, Leto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leto
Context triple: [Letoon, dedicatedTo, Leto]
  • A. Leto chosen
    Leto is a Titaness in Greek mythology best known as the mother of the twin Olympian deities Apollo and Artemis.
  • B. Letňany
    Letňany is a district in the northeastern part of Prague, Czech Republic, known for its residential areas, shopping centers, and transport links including a terminus of the city’s metro system.
  • C. Automne
    Automne is a river in northern France that serves as a tributary of the Oise.
  • D. El Verano
    El Verano is a small community in California’s Sonoma Valley, known for its residential character and proximity to the region’s wineries and historic towns.
  • E. Winters
    Winters is a small agricultural and wine-producing city in Northern California known for its historic downtown and proximity to outdoor recreation areas.
  • 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_69bd4413f9908190afcff44d7929cc4c completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6fa760448190946401b4b21ea8b7 completed March 20, 2026, 4:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6ff19f508190902b77b9ca1e5ab6 completed March 21, 2026, 10:16 a.m.
Created at: March 20, 2026, 1:29 p.m.