Triple

T26212328
Position Surface form Disambiguated ID Type / Status
Subject C. T. C. Wall E655521 entity
Predicate notableWork P4 FINISHED
Object Wall finiteness obstruction
Wall finiteness obstruction is an algebraic topological invariant introduced by C. T. C. Wall that determines whether a space is homotopy equivalent to a finite CW-complex.
E1714629 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: Wall finiteness obstruction | Statement: [C. T. C. Wall, notableWork, Wall finiteness obstruction]
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: Wall finiteness obstruction
Triple: [C. T. C. Wall, notableWork, Wall finiteness obstruction]
Generated description
Wall finiteness obstruction is an algebraic topological invariant introduced by C. T. C. Wall that determines whether a space is homotopy equivalent to a finite CW-complex.

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_69ee5b49adb4819086545280d4ef6337 completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60d1804548190ab0bba3376f28269 completed May 2, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11858b71f48190bd979be75d984930 completed May 23, 2026, 10:46 a.m.
NEDg Description generation batch_6a11865aaac881909aa388f473a6e5a3 completed May 23, 2026, 10:50 a.m.
NED2 Entity disambiguation (via description) batch_6a11873fe9708190a0ad2b27028b120a completed May 23, 2026, 10:53 a.m.
Created at: April 26, 2026, 8:52 p.m.