Triple

T27064402
Position Surface form Disambiguated ID Type / Status
Subject Robert FitzHamon E685132 entity
Predicate child P120 FINISHED
Object Cecilia FitzRobert
Cecilia FitzRobert was a Norman noblewoman of the 12th century, known as the daughter and heiress of magnate Robert FitzHamon and wife of Robert, 1st Earl of Gloucester.
 E1758988 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: Cecilia FitzRobert | Statement: [Robert FitzHamon, child, Cecilia FitzRobert]
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: Cecilia FitzRobert
Triple: [Robert FitzHamon, child, Cecilia FitzRobert]
Generated description
Cecilia FitzRobert was a Norman noblewoman of the 12th century, known as the daughter and heiress of magnate Robert FitzHamon and wife of Robert, 1st Earl of Gloucester.

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_6a1247f9eb5881908278ff3bc201f5ea completed May 24, 2026, 12:36 a.m.
NEDg Description generation batch_6a124bf692708190b52de3df629cb45c completed May 24, 2026, 12:53 a.m.
NED2 Entity disambiguation (via description) batch_6a124c6c11f081908fc85103770dcf9c completed May 24, 2026, 12:55 a.m.
Created at: April 27, 2026, 8:23 a.m.