Triple

T17412736
Position Surface form Disambiguated ID Type / Status
Subject Samuel Smiles E423408 entity
Predicate wrote P2831 FINISHED
Object Thrift 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: Thrift | Statement: [Samuel Smiles, wrote, Thrift]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thrift
Context triple: [Samuel Smiles, wrote, Thrift]
  • A. Thrift
    Thrift is an open-source software framework for scalable cross-language services development, providing an interface definition language and code generation for efficient RPC and data serialization.
  • B. Thrift chosen
    Thrift is a self-help and moral improvement book by Samuel Smiles that promotes industriousness, frugality, and personal responsibility as keys to individual and social progress.
  • C. Thourout
    Thourout is a town in West Flanders, Belgium, historically notable as the place where the French geographer and anarchist Élisée Reclus died.
  • D. Takas
    Takas is a dialect of the Mwaghavul language spoken by a subgroup of the Mwaghavul people in Nigeria’s Plateau State.
  • E. Tarifit
    Tarifit is a Northern Berber language spoken primarily by the Riffian people in the Rif region of northern Morocco.
  • 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_69d889d7d27c819088486ce3f0627fa1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43b0c12b881908b2ddc13678c7a75 completed April 19, 2026, 2:16 a.m.
Created at: April 10, 2026, 5:46 a.m.