Triple

T37560403
Position Surface form Disambiguated ID Type / Status
Subject Night Flight E933803 entity
Predicate originalTitle P65 FINISHED
Object Vol de nuit
Vol de nuit is a 1931 novel by Antoine de Saint-Exupéry that portrays the perilous lives of early airmail pilots in South America and explores themes of duty, sacrifice, and human courage.
E2233111 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: Vol de nuit | Statement: [Night Flight, originalTitle, Vol de nuit]
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: Vol de nuit
Triple: [Night Flight, originalTitle, Vol de nuit]
Generated description
Vol de nuit is a 1931 novel by Antoine de Saint-Exupéry that portrays the perilous lives of early airmail pilots in South America and explores themes of duty, sacrifice, and human courage.

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_69f76ecb4acc8190b53f96d0b013e415 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba459308081908042a0e758818436 completed May 6, 2026, 8:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a409f16541c8190b47947eefb583af7 completed June 28, 2026, 4:12 a.m.
NEDg Description generation batch_6a40a1b08aec8190a4986a8d7a76a42b completed June 28, 2026, 4:23 a.m.
NED2 Entity disambiguation (via description) batch_6a40a20dda508190b4642cafb3af3b9f completed June 28, 2026, 4:24 a.m.
Created at: May 3, 2026, 4:17 p.m.