Triple

T25302133
Position Surface form Disambiguated ID Type / Status
Subject Adelaide of Paris E634372 entity
Predicate saidToBeTheSameAs P39 FINISHED
Object Adelheid of Paris
Adelheid of Paris, also known as Adelaide of Paris, was a 9th-century Frankish noblewoman who became queen consort of the West Franks through her marriage to King Louis the Stammerer.
E1752544 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: Adelheid of Paris | Statement: [Adelaide of Paris, saidToBeTheSameAs, Adelheid of Paris]
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: Adelheid of Paris
Triple: [Adelaide of Paris, saidToBeTheSameAs, Adelheid of Paris]
Generated description
Adelheid of Paris, also known as Adelaide of Paris, was a 9th-century Frankish noblewoman who became queen consort of the West Franks through her marriage to King Louis the Stammerer.

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_69e75a972c6481909bc11710e8d30a6c completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f493968b5c8190bc0108a23b81b38a completed May 1, 2026, 11:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a12296965088190a7ba80f211586754 completed May 23, 2026, 10:25 p.m.
NEDg Description generation batch_6a122ab3c688819090346bce8a20c061 completed May 23, 2026, 10:31 p.m.
NED2 Entity disambiguation (via description) batch_6a122bf0a15c81909e479281bb9e7d73 completed May 23, 2026, 10:36 p.m.
Created at: April 21, 2026, 1:24 p.m.