Triple

T30603731
Position Surface form Disambiguated ID Type / Status
Subject Oliver Sacks E778978 entity
Predicate notableWork P4 FINISHED
Object The Man Who Mistook His Wife for a Hat
The Man Who Mistook His Wife for a Hat is a bestselling collection of clinical tales by neurologist Oliver Sacks that explores unusual neurological disorders through compassionate, narrative case studies.
 E749066 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: The Man Who Mistook His Wife for a Hat | Statement: [Oliver Sacks, notableWork, The Man Who Mistook His Wife for a Hat]
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: The Man Who Mistook His Wife for a Hat
Triple: [Oliver Sacks, notableWork, The Man Who Mistook His Wife for a Hat]
Generated description
The Man Who Mistook His Wife for a Hat is a bestselling collection of clinical tales by neurologist Oliver Sacks that explores unusual neurological disorders through compassionate, narrative case studies.

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_69f224a21fc08190abd9d8dd9eb6bb4c completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f689b47ad08190beba0baceec9341c completed May 2, 2026, 11:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28571d5ce081909739cb3cbb4d729b completed June 9, 2026, 6:10 p.m.
NEDg Description generation batch_6a28597516d481909ebbcd3d2554e7ae completed June 9, 2026, 6:20 p.m.
NED2 Entity disambiguation (via description) batch_6a285a60386081909c73d1ef55aaeb8a completed June 9, 2026, 6:24 p.m.
Created at: April 29, 2026, 8:25 p.m.