Triple

T5513382
Position Surface form Disambiguated ID Type / Status
Subject Horae E144620 entity
Predicate worshipPlace P1191 FINISHED
Object Argos E70939 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: Argos | Statement: [Horae, worshipPlace, Argos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Argos
Context triple: [Horae, worshipPlace, Argos]
  • A. Argos
    Argos is the common nickname for the Toronto Argonauts, a professional Canadian Football League team based in Toronto.
  • B. Argos chosen
    Argos is one of the oldest continuously inhabited cities in Greece, located in the Peloponnese and historically significant as a major center of ancient Greek civilization.
  • C. Argos
    Argos is a major UK-based catalogue and online retailer known for offering a wide range of household goods, electronics, toys, and more through both physical stores and digital channels.
  • D. Argus
    Argus is an early distributed programming language known for pioneering concepts in fault-tolerant, distributed systems and influencing modern object-oriented and concurrent programming.
  • E. Argus
    Argus is a many-eyed giant from Greek mythology best known for his role as a vigilant guardian.
  • 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_69c008f77ff88190b0cd50ca207295d1 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f599d0881909ce86fcc45d4d920 completed March 22, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027d192808190b1e80a6f3be44870 completed March 22, 2026, 5:33 p.m.
Created at: March 22, 2026, 3:33 p.m.