Triple

T26031909
Position Surface form Disambiguated ID Type / Status
Subject Henry Scott, 1st Earl of Deloraine E647452 entity
Predicate nobleTitle P914 FINISHED
Object Earl of Deloraine
The Earl of Deloraine was a Scottish peerage title in the early 18th century, created for Henry Scott, an illegitimate son of King Charles II.
E1704498 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 of Deloraine | Statement: [Henry Scott, 1st Earl of Deloraine, nobleTitle, Earl of Deloraine]
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 of Deloraine
Triple: [Henry Scott, 1st Earl of Deloraine, nobleTitle, Earl of Deloraine]
Generated description
The Earl of Deloraine was a Scottish peerage title in the early 18th century, created for Henry Scott, an illegitimate son of King Charles II.

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_69e77e8b60e88190a3b26c4f0032a2c2 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6061a33f88190897dc485e790c557 completed May 2, 2026, 2:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1107afac0481908e05af071ceae287 completed May 23, 2026, 1:49 a.m.
NEDg Description generation batch_6a1108b862f48190832b132747b84e68 completed May 23, 2026, 1:54 a.m.
NED2 Entity disambiguation (via description) batch_6a1109111b088190933eb70c3e760144 completed May 23, 2026, 1:55 a.m.
Created at: April 22, 2026, 9:06 a.m.