Triple

T32883738
Position Surface form Disambiguated ID Type / Status
Subject Ó Duinnín E841137 entity
Predicate historicallyBorneBy P2834 FINISHED
Object Irish literary families
Irish literary families were hereditary learned dynasties in Gaelic Ireland, renowned for preserving and producing manuscripts, poetry, and scholarship across generations.
 E2027121 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: Irish literary families | Statement: [Ó Duinnín, historicallyBorneBy, Irish literary families]
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: Irish literary families
Triple: [Ó Duinnín, historicallyBorneBy, Irish literary families]
Generated description
Irish literary families were hereditary learned dynasties in Gaelic Ireland, renowned for preserving and producing manuscripts, poetry, and scholarship across generations.

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_69f349446e288190a70c05bcc4d81172 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d03d104481909acbca1f7783f566 completed May 3, 2026, 4:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34c6831fbc8190890ebf98ea5d1c1d completed June 19, 2026, 4:33 a.m.
NEDg Description generation batch_6a34c6fcd63c8190ba9ffdcf1a458924 completed June 19, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_6a34c75aae0c8190a77128522d0c4272 completed June 19, 2026, 4:36 a.m.
Created at: May 1, 2026, 1:18 a.m.