Triple

T30847058
Position Surface form Disambiguated ID Type / Status
Subject Les Noces E785665 entity
Predicate sceneTitle P170558 FINISHED
Object The Blessing of the Bride
"The Blessing of the Bride" is a scene from Igor Stravinsky’s ballet-cantata *Les Noces*, depicting a ritual moment in a traditional Russian peasant wedding.
 E1936954 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: The Blessing of the Bride | Statement: [Les Noces, sceneTitle, The Blessing of the Bride]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: The Blessing of the Bride
Triple: [Les Noces, sceneTitle, The Blessing of the Bride]
Generated description
"The Blessing of the Bride" is a scene from Igor Stravinsky’s ballet-cantata *Les Noces*, depicting a ritual moment in a traditional Russian peasant wedding.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: sceneTitle
Context triple: [Les Noces, sceneTitle, The Blessing of the Bride]
  • A. scenes
    Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
  • B. sceneLabel
    Indicates the categorical label or type assigned to an entire scene based on its overall content or context.
  • C. sceneStatus
    Indicates the current state or condition of a scene within a given context or process.
  • D. showsScene
    Indicates that one entity (such as a media item or visual representation) depicts or presents a particular scene.
  • E. sceneFeature
    Indicates a characteristic, element, or attribute that is present within or helps define a particular scene.
  • F. None of above. chosen

Provenance (7 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_69f224b850848190a4af4ccf8ddadcdf completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6917961ec81908dbd73e67c1ff383 completed May 3, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28c7ceaca48190905652a241fe355d completed June 10, 2026, 2:11 a.m.
NEDg Description generation batch_6a28cb8b39408190975ecbac0c8f0d15 completed June 10, 2026, 2:27 a.m.
NED2 Entity disambiguation (via description) batch_6a28cc6d10c48190b4d80bb129c95229 completed June 10, 2026, 2:31 a.m.
PD Predicate disambiguation batch_69f68b7d2794819092fef8a63f4f3de8 completed May 2, 2026, 11:40 p.m.
PDg Predicate description generation batch_69f68fb914b88190b0cad83ea9fe9dfc completed May 2, 2026, 11:58 p.m.
Created at: April 29, 2026, 8:46 p.m.