Triple

T37000622
Position Surface form Disambiguated ID Type / Status
Subject John III of Egmont E915335 entity
Predicate child P120 FINISHED
Object Floris I, Count of Egmont
Floris I, Count of Egmont was a 15th–16th century Dutch nobleman from the influential House of Egmont who held the title of Count of Egmont and played a role in the politics of the Habsburg Netherlands.
E2211331 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: Floris I, Count of Egmont | Statement: [John III of Egmont, child, Floris I, Count of Egmont]
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: Floris I, Count of Egmont
Triple: [John III of Egmont, child, Floris I, Count of Egmont]
Generated description
Floris I, Count of Egmont was a 15th–16th century Dutch nobleman from the influential House of Egmont who held the title of Count of Egmont and played a role in the politics of the Habsburg Netherlands.

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_69f76e8f1a8c81909db172ed31304971 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9ffea40b881909cb257af4abc850f completed May 5, 2026, 2:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e8c2fae3c8190ab43ee1b959fcd29 completed June 26, 2026, 2:26 p.m.
NEDg Description generation batch_6a3e97770b6881909c3e138a2d8b2994 completed June 26, 2026, 3:15 p.m.
NED2 Entity disambiguation (via description) batch_6a3eeee1a4908190a409ff5d52ccbad2 completed June 26, 2026, 9:28 p.m.
Created at: May 3, 2026, 4:14 p.m.