Triple

T32433426
Position Surface form Disambiguated ID Type / Status
Subject Marquess of Lincolnshire E828788 entity
Predicate higherTitleOf P23605 FINISHED
Object Earl Carrington
Earl Carrington is a British peerage title historically associated with the aristocratic family later elevated to the Marquessate of Lincolnshire.
E827092 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: Earl Carrington | Statement: [Marquess of Lincolnshire, higherTitleOf, Earl Carrington]
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: Earl Carrington
Triple: [Marquess of Lincolnshire, higherTitleOf, Earl Carrington]
Generated description
Earl Carrington is a British peerage title historically associated with the aristocratic family later elevated to the Marquessate of Lincolnshire.

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_69f3491bf298819097b610f772d54a6d completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c2b0108c81908aab3d55aaf9f8e5 completed May 3, 2026, 3:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a347b6ee42081909e7a756e05b62595 completed June 18, 2026, 11:12 p.m.
NEDg Description generation batch_6a347c8c8d1881909646d6cdf1230f78 completed June 18, 2026, 11:17 p.m.
NED2 Entity disambiguation (via description) batch_6a347d6a097881909f078a5dbbdf4e1f completed June 18, 2026, 11:21 p.m.
Created at: May 1, 2026, 12:55 a.m.