Triple

T30815050
Position Surface form Disambiguated ID Type / Status
Subject William Duff, 1st Earl Fife E784752 entity
Predicate ordinalNumber P4901 FINISHED
Object 1st Earl Fife
1st Earl Fife, William Duff, was an 18th-century Scottish nobleman and landowner who became the first holder of the Earldom of Fife in the Peerage of Ireland.
E2131807 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: 1st Earl Fife | Statement: [William Duff, 1st Earl Fife, ordinalNumber, 1st Earl Fife]
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: 1st Earl Fife
Triple: [William Duff, 1st Earl Fife, ordinalNumber, 1st Earl Fife]
Generated description
1st Earl Fife, William Duff, was an 18th-century Scottish nobleman and landowner who became the first holder of the Earldom of Fife in the Peerage of Ireland.

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_69f224b4eda48190bd212ce4f3901e56 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6906745788190b4876420c801757a completed May 3, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3803e29cb08190ae846b7d3395af5d completed June 21, 2026, 3:31 p.m.
NEDg Description generation batch_6a3804fb77788190a62dbb8b24219632 completed June 21, 2026, 3:36 p.m.
NED2 Entity disambiguation (via description) batch_6a38076c7d908190a1bdf1eabfaf026b completed June 21, 2026, 3:46 p.m.
Created at: April 29, 2026, 8:43 p.m.