Triple

T31258026
Position Surface form Disambiguated ID Type / Status
Subject Eóganachta dynasty E797033 entity
Predicate notableMember P10 FINISHED
Object Ólchobar mac Cináeda
Ólchobar mac Cináeda was a 9th-century Irish king of Munster from the Eóganachta dynasty, noted for his role in regional politics and resistance to Viking incursions.
E2186632 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: Ólchobar mac Cináeda | Statement: [Eóganachta dynasty, notableMember, Ólchobar mac Cináeda]
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: Ólchobar mac Cináeda
Triple: [Eóganachta dynasty, notableMember, Ólchobar mac Cináeda]
Generated description
Ólchobar mac Cináeda was a 9th-century Irish king of Munster from the Eóganachta dynasty, noted for his role in regional politics and resistance to Viking incursions.

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_69f224dd5fdc81908a4cd24917b67668 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69d8917348190bda99c6ef3f5c0fb completed May 3, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a39dbaee1208190bd87256d4ad40fdb completed June 23, 2026, 1:04 a.m.
NEDg Description generation batch_6a39dcceb1a081908de121c93a719bad completed June 23, 2026, 1:09 a.m.
NED2 Entity disambiguation (via description) batch_6a39dd3627f48190a70cd2c7a8497aa9 completed June 23, 2026, 1:11 a.m.
Created at: April 29, 2026, 9:12 p.m.