Triple

T37724570
Position Surface form Disambiguated ID Type / Status
Subject hypoxic-ischemic encephalopathy E939681 entity
Predicate isClassifiedBy P25488 FINISHED
Object Sarnat staging
Sarnat staging is a clinical grading system used to assess the severity and progression of neonatal hypoxic-ischemic encephalopathy based on neurological signs and EEG findings.
E2241411 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: Sarnat staging | Statement: [hypoxic-ischemic encephalopathy, isClassifiedBy, Sarnat staging]
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: Sarnat staging
Triple: [hypoxic-ischemic encephalopathy, isClassifiedBy, Sarnat staging]
Generated description
Sarnat staging is a clinical grading system used to assess the severity and progression of neonatal hypoxic-ischemic encephalopathy based on neurological signs and EEG findings.

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_69f76edc208c8190bc8b9683f75e1024 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbae74d67881909d1860c3a4c99602 completed May 6, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40d67df1d8819090bf038521de2c5d completed June 28, 2026, 8:08 a.m.
NEDg Description generation batch_6a40da63f78081908dee41d23c8d4026 completed June 28, 2026, 8:25 a.m.
NED2 Entity disambiguation (via description) batch_6a40db0ab1c481909d3db018dd2b8bde completed June 28, 2026, 8:27 a.m.
Created at: May 3, 2026, 4:18 p.m.