Triple

T24352741
Position Surface form Disambiguated ID Type / Status
Subject Dale Lastman E613837 entity
Predicate employer P7 FINISHED
Object Goodmans LLP
Goodmans LLP is a prominent Canadian business law firm based in Toronto, known for its corporate, M&A, and securities practice.
E1632427 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: Goodmans LLP | Statement: [Dale Lastman, employer, Goodmans LLP]
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: Goodmans LLP
Triple: [Dale Lastman, employer, Goodmans LLP]
Generated description
Goodmans LLP is a prominent Canadian business law firm based in Toronto, known for its corporate, M&A, and securities practice.

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_69e2d7ddd29481909e7f539a6072bd71 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f293467a508190937b9614870e243e completed April 29, 2026, 11:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fd6672ec081909a8dcd6d48644659 completed May 22, 2026, 4:07 a.m.
NEDg Description generation batch_6a0fd76f32f081908122da8e6064e205 completed May 22, 2026, 4:11 a.m.
NED2 Entity disambiguation (via description) batch_6a0fd8e5ce10819096e6cdff28c1b3a2 completed May 22, 2026, 4:17 a.m.
Created at: April 18, 2026, 1:59 a.m.