Triple

T26844635
Position Surface form Disambiguated ID Type / Status
Subject Marquess of Montferrat E675882 entity
Predicate titleHolder P1911 FINISHED
Object John Jacob, Marquess of Montferrat
John Jacob, Marquess of Montferrat, was a nobleman who held the Italian marquessate of Montferrat as part of the high-ranking European aristocracy.
E1821260 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: John Jacob, Marquess of Montferrat | Statement: [Marquess of Montferrat, titleHolder, John Jacob, Marquess of Montferrat]
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: John Jacob, Marquess of Montferrat
Triple: [Marquess of Montferrat, titleHolder, John Jacob, Marquess of Montferrat]
Generated description
John Jacob, Marquess of Montferrat, was a nobleman who held the Italian marquessate of Montferrat as part of the high-ranking European aristocracy.

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_69eee9b8d5e88190a07d3455c0fbb21f completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61b4bb4f88190acd826f0fb9b7c3b completed May 2, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac179f948190ae2d5989bb199d30 completed May 31, 2026, 9:45 p.m.
NEDg Description generation batch_6a1cacd14e048190b6a26e9b5750dff8 completed May 31, 2026, 9:49 p.m.
NED2 Entity disambiguation (via description) batch_6a1cadcb71b081909010e5cbd29beb64 completed May 31, 2026, 9:53 p.m.
Created at: April 27, 2026, 5:10 a.m.