Triple

T25899636
Position Surface form Disambiguated ID Type / Status
Subject Matilda of Leuven E652568 entity
Predicate spouseNobleFamily P25212 FINISHED
Object House of Alsace
The House of Alsace was a medieval noble dynasty that ruled the County (later Duchy) of Alsace and provided influential counts and dukes within the Holy Roman Empire.
E1572277 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: House of Alsace | Statement: [Matilda of Leuven, spouseNobleFamily, House of Alsace]
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: House of Alsace
Triple: [Matilda of Leuven, spouseNobleFamily, House of Alsace]
Generated description
The House of Alsace was a medieval noble dynasty that ruled the County (later Duchy) of Alsace and provided influential counts and dukes within the Holy Roman Empire.

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_69e7ab3c6cc081908de59bfcc28ec19d completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6038843c481909a71270b5846ba65 completed May 2, 2026, 2 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecc4459881908a9612e7ce1bd1aa completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10ef215b448190853f97729867b5fb completed May 23, 2026, 12:04 a.m.
NED2 Entity disambiguation (via description) batch_6a10efc6a0e48190a595a5025ad5c926 completed May 23, 2026, 12:07 a.m.
Created at: April 22, 2026, 8:24 a.m.