Triple

T34277000
Position Surface form Disambiguated ID Type / Status
Subject Charles Stewart, 3rd Duke of Richmond E879485 entity
Predicate aristocraticTitleTerritory P1919 FINISHED
Object Richmond
Richmond is a historic English dukedom and associated territorial designation traditionally linked to the noble title of Duke of Richmond.
E2088785 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: Richmond | Statement: [Charles Stewart, 3rd Duke of Richmond, aristocraticTitleTerritory, Richmond]
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: Richmond
Triple: [Charles Stewart, 3rd Duke of Richmond, aristocraticTitleTerritory, Richmond]
Generated description
Richmond is a historic English dukedom and associated territorial designation traditionally linked to the noble title of Duke of Richmond.

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_69f349b5f6648190b9420d94a4cd16e0 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f712eb74408190b0b9818f5a1916fe completed May 3, 2026, 9:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36e619557081909b8b79259e01abc8 completed June 20, 2026, 7:12 p.m.
NEDg Description generation batch_6a36e6ecf1b08190a12a4aa23672142a completed June 20, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_6a36e7b750708190bb913e8368704235 completed June 20, 2026, 7:19 p.m.
Created at: May 1, 2026, 1:56 a.m.