Triple

T26180523
Position Surface form Disambiguated ID Type / Status
Subject Van der Does family E654665 entity
Predicate hasNotableMember P304 FINISHED
Object Antonius van der Does
Antonius van der Does was a notable member of the Dutch Van der Does family, recognized for his prominence within this historically significant lineage.
E1801064 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: Antonius van der Does | Statement: [Van der Does family, hasNotableMember, Antonius van der Does]
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: Antonius van der Does
Triple: [Van der Does family, hasNotableMember, Antonius van der Does]
Generated description
Antonius van der Does was a notable member of the Dutch Van der Does family, recognized for his prominence within this historically significant lineage.

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_69ee5b45873c81909499203612d05d07 completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60c6f7d4c819087acf8c6de2cc895 completed May 2, 2026, 2:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b8633b008190a102b99892c11876 completed May 26, 2026, 3:12 p.m.
NEDg Description generation batch_6a15bd19b4908190942663430bf54817 completed May 26, 2026, 3:32 p.m.
NED2 Entity disambiguation (via description) batch_6a15bfdf6e7481909276897a678b012b completed May 26, 2026, 3:44 p.m.
Created at: April 26, 2026, 8:39 p.m.