Triple

T12844112
Position Surface form Disambiguated ID Type / Status
Subject Angela Beesley E307127 entity
Predicate givenName P17 FINISHED
Object Angela E211185 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: Angela | Statement: [Angela Beesley, givenName, Angela]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Angela
Context triple: [Angela Beesley, givenName, Angela]
  • A. Angela
    Angela is a character in the British stage play and film "Abigail's Party," known for her polite, somewhat naive demeanor amid the story's tense social dynamics.
  • B. Angela
    Angela is the given name of Angela Merkel, the long-serving former Chancellor of Germany and a prominent European political leader.
  • C. Angela chosen
    Angela is a feminine given name commonly used in many cultures, often associated with meanings related to "angel" or "messenger."
  • D. Angela
    Angela is the heroine of Matthew Lewis's Gothic melodrama "The Castle Spectre," central to its tale of mystery, romance, and supernatural intrigue.
  • E. Angela
    Angela is a character in John Keats’s narrative poem "The Eve of St. Agnes," serving as an elderly attendant who helps facilitate the lovers’ secret meeting.
  • 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_69d7bdf52b94819096d6f0ba4ab50a98 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96ff3a7208190b93f6292ed5efc07 completed April 10, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b9fa40c8190bbc2c6ad22795de4 completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:36 p.m.