Triple

T8763421
Position Surface form Disambiguated ID Type / Status
Subject Muse Watson E208260 entity
Predicate familyName P18 FINISHED
Object Watson E91959 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: Watson | Statement: [Muse Watson, familyName, Watson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Watson
Context triple: [Muse Watson, familyName, Watson]
  • A. Watson chosen
    Watson is a common English surname borne by numerous notable figures, including scientists, artists, and public personalities.
  • B. WATSON
    WATSON is a close-up imaging camera on NASA’s Perseverance rover used to examine the fine details of Martian rocks and surface materials.
  • C. IBM Watson
    IBM Watson is IBM’s artificial intelligence platform known for its natural language processing, machine learning capabilities, and high-profile applications such as winning on Jeopardy! and powering enterprise AI solutions.
  • D. Bixby
    Bixby is a suburban city in northeastern Oklahoma, known for its rapid growth and agricultural roots within the Tulsa metropolitan area.
  • E. Bixby
    Bixby is Samsung's proprietary virtual assistant designed to enable voice control, smart device integration, and contextual assistance across the company's ecosystem of products.
  • 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_69ca835df7e08190ac875664cca8f9ca completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5dfc85e481909a7ce80c5022e6e9 completed March 31, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf435d07148190b9e06d080f99a622 completed April 3, 2026, 4:34 a.m.
Created at: March 30, 2026, 6:40 p.m.