Triple

T31503840
Position Surface form Disambiguated ID Type / Status
Subject House of Leiningen E803760 entity
Predicate hasMember P10 FINISHED
Object Princess Alberta of Leiningen
Princess Alberta of Leiningen was a 19th-century German noblewoman from the mediatized House of Leiningen, a family closely connected by marriage to the British royal family.
E2180642 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: Princess Alberta of Leiningen | Statement: [House of Leiningen, hasMember, Princess Alberta of Leiningen]
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: Princess Alberta of Leiningen
Triple: [House of Leiningen, hasMember, Princess Alberta of Leiningen]
Generated description
Princess Alberta of Leiningen was a 19th-century German noblewoman from the mediatized House of Leiningen, a family closely connected by marriage to the British royal family.

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_69f348cae52081909fa8e5f697523ae3 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a214a24481908d30547f6d36aabe completed May 3, 2026, 1:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a39a2fcbc648190a0b959b87045812a completed June 22, 2026, 9:02 p.m.
NEDg Description generation batch_6a39a71273f08190b348660dd0b556ff completed June 22, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a39a8ee93b88190a63c7a46442ec97d completed June 22, 2026, 9:28 p.m.
Created at: April 30, 2026, 9:46 p.m.