Triple

T30321876
Position Surface form Disambiguated ID Type / Status
Subject Book of Durrow E771222 entity
Predicate alsoKnownAs P39 FINISHED
Object Codex Durmachensis
Codex Durmachensis is an early medieval illuminated manuscript of the Gospels, renowned as one of the oldest surviving examples of Insular art from the British Isles.
E1911184 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: Codex Durmachensis | Statement: [Book of Durrow, alsoKnownAs, Codex Durmachensis]
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: Codex Durmachensis
Triple: [Book of Durrow, alsoKnownAs, Codex Durmachensis]
Generated description
Codex Durmachensis is an early medieval illuminated manuscript of the Gospels, renowned as one of the oldest surviving examples of Insular art from the British Isles.

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_69f22489ee8481909344649bfbb92e83 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68198b7d0819095fcf8607c57247e completed May 2, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a277c1697988190931687a88b8ae11c completed June 9, 2026, 2:36 a.m.
NEDg Description generation batch_6a277db96e588190b880660e62bb2364 completed June 9, 2026, 2:43 a.m.
NED2 Entity disambiguation (via description) batch_6a277e55f0788190b9db58600d6de7d4 completed June 9, 2026, 2:45 a.m.
Created at: April 29, 2026, 7:52 p.m.