Triple

T34794171
Position Surface form Disambiguated ID Type / Status
Subject Gabriel Conroy E1003023 entity
Predicate contrastsWith P278 FINISHED
Object Miss Ivors
Miss Ivors is a politically engaged, nationalist Irish woman in James Joyce’s short story “The Dead,” whose outspoken views and assertive personality sharply oppose Gabriel Conroy’s more reserved, Anglicized outlook.
E2113179 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: Miss Ivors | Statement: [Gabriel Conroy, contrastsWith, Miss Ivors]
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: Miss Ivors
Triple: [Gabriel Conroy, contrastsWith, Miss Ivors]
Generated description
Miss Ivors is a politically engaged, nationalist Irish woman in James Joyce’s short story “The Dead,” whose outspoken views and assertive personality sharply oppose Gabriel Conroy’s more reserved, Anglicized outlook.

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_69f76db543808190b188c6c86a91491b completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77a6544748190b38550b7e2da935d completed May 3, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a376fa3e0e08190be6c829fd8476215 completed June 21, 2026, 4:59 a.m.
NEDg Description generation batch_6a37704fb6948190b7e025cfe56a1ee4 completed June 21, 2026, 5:02 a.m.
NED2 Entity disambiguation (via description) batch_6a37716ab2c48190b7c24792201885c8 completed June 21, 2026, 5:06 a.m.
Created at: May 3, 2026, 3:59 p.m.