Triple

T3926063
Position Surface form Disambiguated ID Type / Status
Subject Monkey & Bear E93277 entity
Predicate followsInTrackList P134 FINISHED
Object Emily E315868 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: Emily | Statement: [Monkey & Bear, followsInTrackList, Emily]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emily
Context triple: [Monkey & Bear, followsInTrackList, Emily]
  • A. Emily
    Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • B. Emily chosen
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • C. Emma
    "Emma" is a 2009 British television miniseries adaptation of Jane Austen's novel, starring Romola Garai in the title role.
  • D. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • E. Jane
    Jane is a powerful vampire in the Twilight series, known for her childlike appearance and her ability to inflict excruciating pain with her mind as a high-ranking enforcer of the Volturi.
  • 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_69aed96bfa1081908f7b30f2c647dee6 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeed7f3cc881909464db1970ba39ae completed March 9, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b52873d5a881909c4c29f06b94a467 completed March 14, 2026, 9:20 a.m.
Created at: March 9, 2026, 3:23 p.m.