Triple

T9330020
Position Surface form Disambiguated ID Type / Status
Subject "Coffee Time" sequence E224491 entity
Predicate songPerformedInSequence P87551 FINISHED
Object Coffee Time E791284 NE FINISHED

How this triple was built (3 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: Coffee Time | Statement: ["Coffee Time" sequence, songPerformedInSequence, Coffee Time]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coffee Time
Context triple: ["Coffee Time" sequence, songPerformedInSequence, Coffee Time]
  • A. Coffee Time chosen
    Coffee Time is a song featured in the "Coffee Time" sequence, likely themed around the rituals or atmosphere of drinking coffee.
  • B. Coffee House Shots
    Coffee House Shots is a political podcast produced by The Spectator that offers rapid analysis and discussion of current UK politics and Westminster gossip.
  • C. Coffee
    Coffee is a popular brewed beverage made from roasted coffee beans, known for its stimulating caffeine content and rich, diverse flavors.
  • D. Coffee
    "Coffee" is a song by the American singer-songwriter Miguel, known for its smooth blend of R&B and sensual, atmospheric production.
  • E. Caffe
    Caffe is an open-source deep learning framework known for its speed and modular design, widely used in computer vision research and applications.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: songPerformedInSequence
Context triple: ["Coffee Time" sequence, songPerformedInSequence, Coffee Time]
  • A. performedSong
    Indicates that an entity (such as an artist or performer) has given a performance of a particular song.
  • B. performedSongFor
    Indicates that one entity performed a song specifically for another entity as the intended audience or recipient.
  • C. singsSongsPerformedBy
    Indicates that one entity sings songs that are performed by another entity.
  • D. performsSongCatalogOf
    Indicates that an entity performs songs that are part of another entity’s song catalog.
  • E. albumSequence
    Indicates that one album directly follows another in a defined ordered sequence, such as a discography or series.
  • F. None of above. chosen

Provenance (5 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_69ca8427a0c08190b749831d5ea98f02 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd37acbc04819092a67d7f392c74cd completed April 1, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e3c30ba88190b192621928136b87 completed April 4, 2026, 10:11 a.m.
PD Predicate disambiguation batch_69cc7a643924819097f01144734901cf completed April 1, 2026, 1:52 a.m.
PDg Predicate description generation batch_69cc94b796788190816b71b1e9996288 completed April 1, 2026, 3:44 a.m.
Created at: March 30, 2026, 7:39 p.m.