Triple

T31503935
Position Surface form Disambiguated ID Type / Status
Subject Counts of Leiningen E803763 entity
Predicate hasTitleHolder P1911 FINISHED
Object Ernst of Leiningen
Ernst of Leiningen was a German nobleman from the House of Leiningen who held the hereditary title of Count within this historic Rhineland-Palatinate dynasty.
E1992020 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: Ernst of Leiningen | Statement: [Counts of Leiningen, hasTitleHolder, Ernst 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: Ernst of Leiningen
Triple: [Counts of Leiningen, hasTitleHolder, Ernst of Leiningen]
Generated description
Ernst of Leiningen was a German nobleman from the House of Leiningen who held the hereditary title of Count within this historic Rhineland-Palatinate dynasty.

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_6a2eddc1ec248190a4750a057914df70 completed June 14, 2026, 4:58 p.m.
NEDg Description generation batch_6a2ee84a3b3c8190ad1548b8ec79d8ee completed June 14, 2026, 5:43 p.m.
NED2 Entity disambiguation (via description) batch_6a2ee949c2a8819099d9884b497be45c completed June 14, 2026, 5:47 p.m.
Created at: April 30, 2026, 9:46 p.m.