Triple

T25902102
Position Surface form Disambiguated ID Type / Status
Subject Chayse Irvin E652643 entity
Predicate workedOn P3 FINISHED
Object Beyoncé: Love Drought
"Beyoncé: Love Drought" is a visually striking music video segment from Beyoncé’s acclaimed visual album "Lemonade," noted for its poetic imagery and emotional exploration of betrayal and reconciliation.
E1700253 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: Beyoncé: Love Drought | Statement: [Chayse Irvin, workedOn, Beyoncé: Love Drought]
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: Beyoncé: Love Drought
Triple: [Chayse Irvin, workedOn, Beyoncé: Love Drought]
Generated description
"Beyoncé: Love Drought" is a visually striking music video segment from Beyoncé’s acclaimed visual album "Lemonade," noted for its poetic imagery and emotional exploration of betrayal and reconciliation.

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_69e7ab3d3f8481909bc53ed64c06af33 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f603bb02288190b40cedbed5b9651d completed May 2, 2026, 2:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecc608b88190a1803c872c33470a completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10f0b022ac8190be810844615f7c9d completed May 23, 2026, 12:11 a.m.
NED2 Entity disambiguation (via description) batch_6a10f10b8b5c81909de43e087f369b53 completed May 23, 2026, 12:12 a.m.
Created at: April 22, 2026, 8:26 a.m.