Triple

T28277782
Position Surface form Disambiguated ID Type / Status
Subject Jacobite court in exile E713050 entity
Predicate hasMember P10 FINISHED
Object John Murray of Broughton
John Murray of Broughton was a prominent Scottish Jacobite who served as secretary to Charles Edward Stuart during the 1745 rising before later turning government informer.
 E1817375 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 Murray of Broughton | Statement: [Jacobite court in exile, hasMember, John Murray of Broughton]
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 Murray of Broughton
Triple: [Jacobite court in exile, hasMember, John Murray of Broughton]
Generated description
John Murray of Broughton was a prominent Scottish Jacobite who served as secretary to Charles Edward Stuart during the 1745 rising before later turning government informer.

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_69efb52275788190ae5181ccebef18ce completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f6444d26948190a5d87f6b105c86cf completed May 2, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1632ecc5208190aa0a33381bdcc109 completed May 26, 2026, 11:55 p.m.
NEDg Description generation batch_6a1633f6ab3c819084c6626f012a75da completed May 26, 2026, 11:59 p.m.
NED2 Entity disambiguation (via description) batch_6a16350e130c8190a9a73ee1edce0928 completed May 27, 2026, 12:04 a.m.
Created at: April 27, 2026, 11:20 p.m.