Triple

T9501052
Position Surface form Disambiguated ID Type / Status
Subject Gregorio E229139 entity
Predicate derivedFrom P909 FINISHED
Object Gregory E50625 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: Gregory | Statement: [Gregorio, derivedFrom, Gregory]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gregory
Context triple: [Gregorio, derivedFrom, Gregory]
  • A. Gregory chosen
    Gregory is a masculine given name of Greek origin, historically associated with figures such as the American actor Gregory Peck.
  • B. Gregory
    Gregory is an electoral district in Queensland, Australia, known for its vast rural area and strong agricultural and mining industries.
  • C. Gerard
    Gerard is a masculine given name of Germanic origin, commonly used in various European countries.
  • D. Grigor
    Grigor is a given name, commonly used in various Eastern European and Caucasian cultures, that corresponds to the English name Gregory.
  • E. Gregorio
    Gregorio is a masculine given name of Latin origin, commonly used in Spanish and Italian-speaking cultures and derived from the name Gregory.
  • 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_69ca84753660819098e8d416e89e26ae completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd983d4b708190a4dfef1246986a26 completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a0a5ec881908bb1643d2bea2c9f completed April 4, 2026, 4:19 p.m.
Created at: March 30, 2026, 7:57 p.m.