Triple

T37175393
Position Surface form Disambiguated ID Type / Status
Subject Simon Ramsay, 16th Earl of Dalhousie E921026 entity
Predicate givenName P17 FINISHED
Object Simon
Simon is a male given name of Hebrew origin, commonly used in English-speaking countries and across Europe.
E449149 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: Simon | Statement: [Simon Ramsay, 16th Earl of Dalhousie, givenName, Simon]
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: Simon
Triple: [Simon Ramsay, 16th Earl of Dalhousie, givenName, Simon]
Generated description
Simon is a male given name of Hebrew origin, commonly used in English-speaking countries and across Europe.

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_69f76ea16f288190b445aa1604d996f4 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb35ec7e0c8190b7eeb0571c2b79a0 completed May 6, 2026, 12:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a402ba84cc48190805ab6be60a43b09 completed June 27, 2026, 7:59 p.m.
NEDg Description generation batch_6a402c8dca0c819092bd1da33f9e0f8f completed June 27, 2026, 8:03 p.m.
NED2 Entity disambiguation (via description) batch_6a402ce66ffc8190bd954782e32160eb completed June 27, 2026, 8:04 p.m.
Created at: May 3, 2026, 4:15 p.m.