Triple

T17994011
Position Surface form Disambiguated ID Type / Status
Subject Elliott H. Lieb E430452 entity
Predicate doctoralAdvisor P167 FINISHED
Object Samuel F. Edwards
Samuel F. Edwards was a prominent British theoretical physicist known for his pioneering work in condensed matter and polymer physics.
E2191990 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: Samuel F. Edwards | Statement: [Elliott H. Lieb, doctoralAdvisor, Samuel F. Edwards]
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: Samuel F. Edwards
Triple: [Elliott H. Lieb, doctoralAdvisor, Samuel F. Edwards]
Generated description
Samuel F. Edwards was a prominent British theoretical physicist known for his pioneering work in condensed matter and polymer physics.

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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b3e29490819090ff221e7d7a9ddd completed April 19, 2026, 10:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3a0938257081908a34f533c8601057 completed June 23, 2026, 4:19 a.m.
NEDg Description generation batch_6a3a0bbb76ec8190a93578ed3265ccf0 completed June 23, 2026, 4:29 a.m.
NED2 Entity disambiguation (via description) batch_6a3a0c1709308190ab8d54e08845c2d5 completed June 23, 2026, 4:31 a.m.
Created at: April 10, 2026, 10:23 a.m.