Triple

T35223481
Position Surface form Disambiguated ID Type / Status
Subject Honoré II, Prince of Monaco E1017023 entity
Predicate mother P120 FINISHED
Object Maria Landi
Maria Landi was an Italian noblewoman of the late 16th century who became part of the ruling family of Monaco as the mother of Honoré II, the principality’s first sovereign prince.
E2136261 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: Maria Landi | Statement: [Honoré II, Prince of Monaco, mother, Maria Landi]
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: Maria Landi
Triple: [Honoré II, Prince of Monaco, mother, Maria Landi]
Generated description
Maria Landi was an Italian noblewoman of the late 16th century who became part of the ruling family of Monaco as the mother of Honoré II, the principality’s first sovereign prince.

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_69f76de072908190ab65038a8a7b6a79 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78ea4af848190bb2201d4096c6e21 completed May 3, 2026, 6:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3823b27d008190b823f35d1d9360d9 completed June 21, 2026, 5:47 p.m.
NEDg Description generation batch_6a382496eb30819081ec6e3c0f8c7137 completed June 21, 2026, 5:51 p.m.
NED2 Entity disambiguation (via description) batch_6a3825d213688190aefa08d3d21f6b75 completed June 21, 2026, 5:56 p.m.
Created at: May 3, 2026, 4:02 p.m.