Triple

T27144573
Position Surface form Disambiguated ID Type / Status
Subject Dubhghlas de hÍde E681906 entity
Predicate spouse P13 FINISHED
Object Lucy Kurtz
Lucy Kurtz was the wife of Dubhghlas de hÍde, the first President of Ireland and a leading figure in the Irish cultural revival.
E1759909 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: Lucy Kurtz | Statement: [Dubhghlas de hÍde, spouse, Lucy Kurtz]
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: Lucy Kurtz
Triple: [Dubhghlas de hÍde, spouse, Lucy Kurtz]
Generated description
Lucy Kurtz was the wife of Dubhghlas de hÍde, the first President of Ireland and a leading figure in the Irish cultural revival.

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_69eefacca3888190b67238d380e8f28b completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f624c4e26c8190baa7d2e28c60be52 completed May 2, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12537ce3608190b6f4b1e77a09292f completed May 24, 2026, 1:25 a.m.
NEDg Description generation batch_6a12556ad52c8190a5f3549c8ce6bdc4 completed May 24, 2026, 1:33 a.m.
NED2 Entity disambiguation (via description) batch_6a1255ae6dc4819080c51cc112f2fd82 completed May 24, 2026, 1:34 a.m.
Created at: April 27, 2026, 9:10 a.m.