Triple

T29477817
Position Surface form Disambiguated ID Type / Status
Subject Oshin of Lampron E747696 entity
Predicate title P38 FINISHED
Object Lord of Lampron
Lord of Lampron was a noble title in the Armenian Kingdom of Cilicia associated with the powerful Lampron dynasty, notably held by the influential baron Oshin of Lampron.
E1583342 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: Lord of Lampron | Statement: [Oshin of Lampron, title, Lord of Lampron]
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: Lord of Lampron
Triple: [Oshin of Lampron, title, Lord of Lampron]
Generated description
Lord of Lampron was a noble title in the Armenian Kingdom of Cilicia associated with the powerful Lampron dynasty, notably held by the influential baron Oshin of Lampron.

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_69f0bd42cf308190bb01b20bc5b7c2d0 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66bd57cac81909e92d58fb91b4a5c completed May 2, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f1204e008190aa0f047e3d0282ab completed June 7, 2026, 10:30 p.m.
NEDg Description generation batch_6a25f6707314819083def6f08c503c36 completed June 7, 2026, 10:53 p.m.
NED2 Entity disambiguation (via description) batch_6a25fab29d588190a93a4b1043036423 completed June 7, 2026, 11:11 p.m.
Created at: April 28, 2026, 4:01 p.m.