Triple

T27064388
Position Surface form Disambiguated ID Type / Status
Subject Robert FitzHamon E685132 entity
Predicate father P120 FINISHED
Object Hamon de Creully
Hamon de Creully was a Norman nobleman of the 11th century, known as the son and heir of the influential lord Robert FitzHamon and a member of the Anglo-Norman aristocracy.
 E1781470 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: Hamon de Creully | Statement: [Robert FitzHamon, father, Hamon de Creully]
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: Hamon de Creully
Triple: [Robert FitzHamon, father, Hamon de Creully]
Generated description
Hamon de Creully was a Norman nobleman of the 11th century, known as the son and heir of the influential lord Robert FitzHamon and a member of the Anglo-Norman aristocracy.

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_69ef14835fcc81908bd737b4267ae528 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f622e734a881908ac15e64575c69d4 completed May 2, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0b1c7c481908ddede2be56cc4b1 completed May 24, 2026, 10:19 a.m.
NEDg Description generation batch_6a12d2afe2208190b03bed8f48920338 completed May 24, 2026, 10:28 a.m.
NED2 Entity disambiguation (via description) batch_6a12d30f0cf08190b69f5abbcd16d27f completed May 24, 2026, 10:29 a.m.
Created at: April 27, 2026, 8:23 a.m.