Triple

T36876584
Position Surface form Disambiguated ID Type / Status
Subject Godbillon–Vey invariant E911357 entity
Predicate relatedTo P37 FINISHED
Object Bott–Haefliger cohomology
Bott–Haefliger cohomology is a cohomology theory for the classifying space of foliations that captures characteristic classes of foliated manifolds, including invariants like the Godbillon–Vey class.
 E2202534 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: Bott–Haefliger cohomology | Statement: [Godbillon–Vey invariant, relatedTo, Bott–Haefliger cohomology]
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: Bott–Haefliger cohomology
Triple: [Godbillon–Vey invariant, relatedTo, Bott–Haefliger cohomology]
Generated description
Bott–Haefliger cohomology is a cohomology theory for the classifying space of foliations that captures characteristic classes of foliated manifolds, including invariants like the Godbillon–Vey class.

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_69f76e82339881909607a65c0503d941 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7cff72b288190bcf7f370edb91503 completed May 3, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfae9b5cc81909b67520b22ba81ec completed June 26, 2026, 4:07 a.m.
NEDg Description generation batch_6a3dfb65339c8190b9dce70882b43218 completed June 26, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_6a3dfcd781f881908480874f47984022 completed June 26, 2026, 4:15 a.m.
Created at: May 3, 2026, 4:13 p.m.