Triple

T23417436
Position Surface form Disambiguated ID Type / Status
Subject Bristol Myers Squibb E560549 entity
Predicate foundedBy P104 FINISHED
Object Edward Robinson Squibb
Edward Robinson Squibb was a 19th-century American physician and pharmaceutical pioneer whose work in producing high-quality medicines led to the creation of one of the companies that later became Bristol Myers Squibb.
E1594494 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: Edward Robinson Squibb | Statement: [Bristol Myers Squibb, foundedBy, Edward Robinson Squibb]
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: Edward Robinson Squibb
Triple: [Bristol Myers Squibb, foundedBy, Edward Robinson Squibb]
Generated description
Edward Robinson Squibb was a 19th-century American physician and pharmaceutical pioneer whose work in producing high-quality medicines led to the creation of one of the companies that later became Bristol Myers Squibb.

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_69e2454cb1108190ab21ada5411a7146 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1a516d158819081e9710b4e372a21 completed April 29, 2026, 6:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f454607108190aca49837dd3d7e31 completed May 21, 2026, 5:47 p.m.
NEDg Description generation batch_6a0f46d5885c819098231e2178e6606e completed May 21, 2026, 5:54 p.m.
NED2 Entity disambiguation (via description) batch_6a0f47b410e8819093c7578df50bd669 completed May 21, 2026, 5:58 p.m.
Created at: April 17, 2026, 5:39 p.m.