Triple

T31142750
Position Surface form Disambiguated ID Type / Status
Subject Banshenchas E793832 entity
Predicate relatedWork P37 FINISHED
Object Lebor na nGenealach
Lebor na nGenealach is a 17th-century Irish genealogical manuscript compiled by Dubhaltach Mac Fhirbhisigh, preserving extensive lineages of Gaelic and Anglo-Norman families.
E1951238 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: Lebor na nGenealach | Statement: [Banshenchas, relatedWork, Lebor na nGenealach]
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: Lebor na nGenealach
Triple: [Banshenchas, relatedWork, Lebor na nGenealach]
Generated description
Lebor na nGenealach is a 17th-century Irish genealogical manuscript compiled by Dubhaltach Mac Fhirbhisigh, preserving extensive lineages of Gaelic and Anglo-Norman families.

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_69f224d2b3a48190aa9dd26fbf6eab1a completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f697974e4c819090a4e708a25055d8 completed May 3, 2026, 12:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a295903cbbc81909e02d6093acab5cc completed June 10, 2026, 12:30 p.m.
NEDg Description generation batch_6a295d01b09c8190a87c2ed99d745566 completed June 10, 2026, 12:48 p.m.
NED2 Entity disambiguation (via description) batch_6a2960ee531881908fe084e5dd959317 completed June 10, 2026, 1:04 p.m.
Created at: April 29, 2026, 9:06 p.m.