Triple

T4270713
Position Surface form Disambiguated ID Type / Status
Subject Generation of Animals E96934 entity
Predicate influenced P9 FINISHED
Object Galen E151145 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: Galen | Statement: [Generation of Animals, influenced, Galen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Galen
Context triple: [Generation of Animals, influenced, Galen]
  • A. Galen chosen
    Galen was a prominent Greek physician, surgeon, and philosopher in the Roman Empire whose medical writings dominated European medicine for over a millennium.
  • B. Dioscorus of Alexandria
    Dioscorus of Alexandria was a 5th-century Coptic patriarch of Alexandria whose controversial leadership and Christological views played a central role in the theological conflicts surrounding the Council of Chalcedon.
  • C. Dorotheus
    Dorotheus was a 6th-century Byzantine jurist who helped systematize and codify Roman law under Emperor Justinian I.
  • D. Dorotheus
    Dorotheus is a relatively obscure historical or religious figure known primarily through their association with Theophilus.
  • E. Hippocrates of Gela
    Hippocrates of Gela was a powerful early 5th-century BC tyrant of the Sicilian city of Gela, known for expanding its territory and influence through military campaigns.
  • 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_69b34543f06c8190915ebb1a4574ffa9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ffb85a88190af000b94673bff59 completed March 12, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7a456108190afa46344a5ed2118 completed March 14, 2026, 7:31 p.m.
Created at: March 12, 2026, 11:07 p.m.