Triple

T26588405
Position Surface form Disambiguated ID Type / Status
Subject de Vaux family E667275 entity
Predicate heldTitle P8 FINISHED
Object Lord of Gilsland
Lord of Gilsland was a medieval feudal title associated with the barony of Gilsland on the Anglo-Scottish border, historically controlled by prominent noble families in northern England.
E1731678 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: Lord of Gilsland | Statement: [de Vaux family, heldTitle, Lord of Gilsland]
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: Lord of Gilsland
Triple: [de Vaux family, heldTitle, Lord of Gilsland]
Generated description
Lord of Gilsland was a medieval feudal title associated with the barony of Gilsland on the Anglo-Scottish border, historically controlled by prominent noble families in northern England.

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_69ee9cfb7e548190b60a9031182f5a7e completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f615237a708190bde157669226dbf0 completed May 2, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c838cb388190a6be7088e3155c68 completed May 23, 2026, 3:31 p.m.
NEDg Description generation batch_6a11c945273c8190ac0bc6fe508a6d9a completed May 23, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a11ca61b1408190ab4bda33e53cb27c completed May 23, 2026, 3:40 p.m.
Created at: April 27, 2026, 2:06 a.m.