Triple

T24024077
Position Surface form Disambiguated ID Type / Status
Subject Hatton E594902 entity
Predicate hasNotableBearer P458 FINISHED
Object Denis Hatton
Denis Hatton is an individual notable enough to be recognized as a bearer of the surname Hatton, though specific widely known public details about him are not readily available.
E1634118 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: Denis Hatton | Statement: [Hatton, hasNotableBearer, Denis Hatton]
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: Denis Hatton
Triple: [Hatton, hasNotableBearer, Denis Hatton]
Generated description
Denis Hatton is an individual notable enough to be recognized as a bearer of the surname Hatton, though specific widely known public details about him are not readily available.

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_69e288be2c288190a3a46006945557f7 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d769f7248190ae145218fb0e8bbd completed April 29, 2026, 10:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe3386b0c81909009f53e1bd2cb9f completed May 22, 2026, 5:01 a.m.
NEDg Description generation batch_6a0fe464435c8190aed7a4a6496ab3f5 completed May 22, 2026, 5:06 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe55f1c888190864ef29ab6945f5a completed May 22, 2026, 5:10 a.m.
Created at: April 17, 2026, 9:53 p.m.