Triple

T26441024
Position Surface form Disambiguated ID Type / Status
Subject Lickorish E665086 entity
Predicate notableWork P4 FINISHED
Object Lickorish–Wallace theorem
The Lickorish–Wallace theorem is a fundamental result in 3-manifold topology stating that every closed, orientable 3-manifold can be obtained by performing Dehn surgery on a link in the 3-sphere.
 E1723987 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: Lickorish–Wallace theorem | Statement: [Lickorish, notableWork, Lickorish–Wallace theorem]
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: Lickorish–Wallace theorem
Triple: [Lickorish, notableWork, Lickorish–Wallace theorem]
Generated description
The Lickorish–Wallace theorem is a fundamental result in 3-manifold topology stating that every closed, orientable 3-manifold can be obtained by performing Dehn surgery on a link in the 3-sphere.

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_69ee883c851881909e2ab04efbb3c5fe completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f6121ae1a0819083492db2e6863175 completed May 2, 2026, 3:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aecf90d48190ba4e6c51147c58c2 completed May 23, 2026, 1:42 p.m.
NEDg Description generation batch_6a11afe8cf308190b39d8d3b270282a7 completed May 23, 2026, 1:47 p.m.
NED2 Entity disambiguation (via description) batch_6a11b071a8c48190a3b486d471e3e1a1 completed May 23, 2026, 1:49 p.m.
Created at: April 26, 2026, 11:58 p.m.