Triple

T28748528
Position Surface form Disambiguated ID Type / Status
Subject Feighner criteria E731448 entity
Predicate includesCategory P1393 FINISHED
Object anorexia nervosa
Anorexia nervosa is a serious eating disorder characterized by self-induced weight loss, distorted body image, and an intense fear of gaining weight, often leading to severe medical complications.
E1832097 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: anorexia nervosa | Statement: [Feighner criteria, includesCategory, anorexia nervosa]
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: anorexia nervosa
Triple: [Feighner criteria, includesCategory, anorexia nervosa]
Generated description
Anorexia nervosa is a serious eating disorder characterized by self-induced weight loss, distorted body image, and an intense fear of gaining weight, often leading to severe medical complications.

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_69f043ecb5c081909ec9da1172d68ece completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f657b9c36481909d9bf07c60c3dcce completed May 2, 2026, 7:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1ccf7061f48190b82649a9d8ff5f80 completed June 1, 2026, 12:16 a.m.
NEDg Description generation batch_6a249438b9c88190bb05682be9349afb completed June 6, 2026, 9:42 p.m.
NED2 Entity disambiguation (via description) batch_6a2498ce9614819086c21dc9dc0b45ea completed June 6, 2026, 10:01 p.m.
Created at: April 28, 2026, 6:06 a.m.