Triple

T7192306
Position Surface form Disambiguated ID Type / Status
Subject Watts E167722 entity
Predicate relatedName P3889 FINISHED
Object Watt E501013 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: Watt | Statement: [Watts, relatedName, Watt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Watt
Context triple: [Watts, relatedName, Watt]
  • A. Watt
    Watt is an experimental novel by Samuel Beckett that follows the absurd, often comic journey of its title character through a bizarre and logically distorted world.
  • B. Watt (character) chosen
    Watt (character) is a fictional protagonist best known as the central figure in Samuel Beckett’s novel "Watt," noted for its absurdist style and exploration of logic and language.
  • C. Amper
    The Amper is a river in Bavaria, Germany, known for flowing from the Ammersee toward the Isar and ultimately contributing to the Danube river system.
  • D. Maxwell
    Maxwell is the given first name of Lord Beaverbrook, a prominent 20th-century British-Canadian newspaper magnate and politician.
  • E. Maxwell
    Maxwell is the middle name of William M. Evarts, a prominent 19th-century American lawyer, statesman, and U.S. Secretary of State.
  • 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_69c6888b5248819090499a884ee3ec39 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e901ea1481908a9e44f96dd4b553 completed March 27, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bf95a1a0819099d252f037c318c7 completed March 28, 2026, 11:46 a.m.
Created at: March 27, 2026, 2:50 p.m.