Triple

T37941398
Position Surface form Disambiguated ID Type / Status
Subject Mafalda of Savoy E946496 entity
Predicate spouse P13 FINISHED
Object Philipp, Landgrave of Hesse
Philipp, Landgrave of Hesse was a German nobleman and head of the House of Hesse who ruled the Hesse region during the early 20th century and was notably connected by marriage to several European royal families.
E2281816 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: Philipp, Landgrave of Hesse | Statement: [Mafalda of Savoy, spouse, Philipp, Landgrave of Hesse]
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: Philipp, Landgrave of Hesse
Triple: [Mafalda of Savoy, spouse, Philipp, Landgrave of Hesse]
Generated description
Philipp, Landgrave of Hesse was a German nobleman and head of the House of Hesse who ruled the Hesse region during the early 20th century and was notably connected by marriage to several European royal families.

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_69f76ef531ac8190ae6d99e5786e76ec completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbdb233d88190a53e82e5bf90262e completed May 6, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a420df4155c81909cf52d51f82a0919 completed June 29, 2026, 6:17 a.m.
NEDg Description generation batch_6a420f2bce788190af3fcce34cd0ad20 completed June 29, 2026, 6:22 a.m.
NED2 Entity disambiguation (via description) batch_6a420f9b2df481908f700fd67351b6c8 completed June 29, 2026, 6:24 a.m.
Created at: May 3, 2026, 4:20 p.m.