Triple

T38562565
Position Surface form Disambiguated ID Type / Status
Subject Margaret McNair Stokes E928117 entity
Predicate sibling P363 FINISHED
Object Whitley Stokes (Celtic scholar)
Whitley Stokes was a prominent 19th-century Irish Celtic scholar and lawyer renowned for his pioneering editions and translations of early Irish texts.
 E2275216 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: Whitley Stokes (Celtic scholar) | Statement: [Margaret McNair Stokes, sibling, Whitley Stokes (Celtic scholar)]
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: Whitley Stokes (Celtic scholar)
Triple: [Margaret McNair Stokes, sibling, Whitley Stokes (Celtic scholar)]
Generated description
Whitley Stokes was a prominent 19th-century Irish Celtic scholar and lawyer renowned for his pioneering editions and translations of early Irish texts.

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_69f76eb8d1808190a588af29d8b266d6 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd90627e481909d66e5110962f167 completed May 7, 2026, 6:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41e04369548190b5115a4868ed1cb6 completed June 29, 2026, 3:02 a.m.
NEDg Description generation batch_6a41e211cc7c81908b15df4b28d8f2a6 completed June 29, 2026, 3:10 a.m.
NED2 Entity disambiguation (via description) batch_6a41e3b3185c8190849330402cf46bab completed June 29, 2026, 3:17 a.m.
Created at: May 3, 2026, 4:32 p.m.