Triple

T17047701
Position Surface form Disambiguated ID Type / Status
Subject All’s Well That Ends Well E413612 entity
Predicate mainCharacter P1183 FINISHED
Object Bertram E13385 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: Bertram | Statement: [All’s Well That Ends Well, mainCharacter, Bertram]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bertram
Context triple: [All’s Well That Ends Well, mainCharacter, Bertram]
  • A. Bertram chosen
    Bertram is a masculine given name of Germanic origin, historically associated with nobility and later borne by various notable figures in arts, architecture, and literature.
  • B. Bertram Ramsay
    Bertram Ramsay was a British admiral who played a key role in planning and directing major Allied naval operations during World War II, including the Dunkirk evacuation and the D-Day landings.
  • C. Eustace
    Eustace is an English-language surname of likely Norman or medieval European origin, borne by various individuals and families.
  • D. Eustace
    Eustace is a masculine given name of Greek origin, historically associated with early Christian saints and medieval European usage.
  • E. Bertram Raphael
    Bertram Raphael is an American computer scientist and artificial intelligence pioneer known for his work in automated reasoning and early AI research at institutions such as SRI International.
  • 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_69d886cd18288190b006abab23f811b7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3da9f799c8190a683ae38cd990643 completed April 18, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01233fb8d88190a9a6ef6a2f19a499 completed May 11, 2026, 12:30 a.m.
Created at: April 10, 2026, 5:34 a.m.