Triple

T38148309
Position Surface form Disambiguated ID Type / Status
Subject Donagh MacCarthy, Viscount Muskerry E952681 entity
Predicate nobleTitle P914 FINISHED
Object Viscount Muskerry
Viscount Muskerry is an Irish noble title historically associated with the MacCarthy family, prominent in the region of Muskerry in County Cork.
E2258789 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: Viscount Muskerry | Statement: [Donagh MacCarthy, Viscount Muskerry, nobleTitle, Viscount Muskerry]
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: Viscount Muskerry
Triple: [Donagh MacCarthy, Viscount Muskerry, nobleTitle, Viscount Muskerry]
Generated description
Viscount Muskerry is an Irish noble title historically associated with the MacCarthy family, prominent in the region of Muskerry in County Cork.

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_69f76f0a67f4819080c492f61d688fcc completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc462d13d08190a90114f40dd4b25a completed May 7, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a417b28ed58819094b603d6f657d4b7 completed June 28, 2026, 7:51 p.m.
NEDg Description generation batch_6a417bbc82a881909b53b621a1d2c079 completed June 28, 2026, 7:53 p.m.
NED2 Entity disambiguation (via description) batch_6a417c16ebd48190bb8d62e0325bfa4a completed June 28, 2026, 7:55 p.m.
Created at: May 3, 2026, 4:21 p.m.