Triple

T32139855
Position Surface form Disambiguated ID Type / Status
Subject Night Sky with Exit Wounds E820872 entity
Predicate notablePoem P4 FINISHED
Object Aubade with Burning City
"Aubade with Burning City" is a widely acclaimed poem by Ocean Vuong that juxtaposes intimate human connection with the violent fall of Saigon during the Vietnam War.
 E1993679 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: Aubade with Burning City | Statement: [Night Sky with Exit Wounds, notablePoem, Aubade with Burning City]
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: Aubade with Burning City
Triple: [Night Sky with Exit Wounds, notablePoem, Aubade with Burning City]
Generated description
"Aubade with Burning City" is a widely acclaimed poem by Ocean Vuong that juxtaposes intimate human connection with the violent fall of Saigon during the Vietnam War.

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_69f349039e0c819091c7a7d322e3f46d completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b9ac2c888190b71f32fd71c58b72 completed May 3, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f013da36481908c18124d4143f973 completed June 14, 2026, 7:30 p.m.
NEDg Description generation batch_6a2f01fe7008819091d5a73abe7ea366 completed June 14, 2026, 7:33 p.m.
NED2 Entity disambiguation (via description) batch_6a2f035270508190bff756fef3523976 completed June 14, 2026, 7:38 p.m.
Created at: May 1, 2026, 12:30 a.m.