Triple

T33823056
Position Surface form Disambiguated ID Type / Status
Subject Harriet Hale E866885 entity
Predicate spouseName P13 FINISHED
Object Lawrence Dundas
Lawrence Dundas was a member of the prominent Dundas family of British aristocrats and politicians, known for holding titles such as Earl or Marquess of Zetland and for his role in 18th–19th century public life.
E2069677 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: Lawrence Dundas | Statement: [Harriet Hale, spouseName, Lawrence Dundas]
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: Lawrence Dundas
Triple: [Harriet Hale, spouseName, Lawrence Dundas]
Generated description
Lawrence Dundas was a member of the prominent Dundas family of British aristocrats and politicians, known for holding titles such as Earl or Marquess of Zetland and for his role in 18th–19th century public life.

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_69f34991dd248190a659541588506b3c completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fffe0ed88190a0d20c37f386cf6e completed May 3, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a366ea0cd6081908e966a41c64d29c8 completed June 20, 2026, 10:42 a.m.
NEDg Description generation batch_6a366f697ba4819087c98bacf069e707 completed June 20, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a3670cc13ec8190975f7d3bc74eb00f completed June 20, 2026, 10:51 a.m.
Created at: May 1, 2026, 1:46 a.m.