Triple

T32453503
Position Surface form Disambiguated ID Type / Status
Subject Tennyson's 1842 Poems collection E829358 entity
Predicate containsWork P2011 FINISHED
Object The Miller’s Daughter
The Miller’s Daughter is a narrative poem by Alfred, Lord Tennyson that tells a romantic, pastoral story of love and rural life.
 E2008796 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: The Miller’s Daughter | Statement: [Tennyson's 1842 Poems collection, containsWork, The Miller’s Daughter]
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: The Miller’s Daughter
Triple: [Tennyson's 1842 Poems collection, containsWork, The Miller’s Daughter]
Generated description
The Miller’s Daughter is a narrative poem by Alfred, Lord Tennyson that tells a romantic, pastoral story of love and rural life.

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_69f3491df9288190afc0b23b1d6e72ce completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c3147ff88190bb4108e817e4eeb1 completed May 3, 2026, 3:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34668bd50081908b32e4146b494e49 completed June 18, 2026, 9:43 p.m.
NEDg Description generation batch_6a3468104f4c8190bfae60a51dee0b35 completed June 18, 2026, 9:50 p.m.
NED2 Entity disambiguation (via description) batch_6a346ae8a91081909a10179607fe69a8 completed June 18, 2026, 10:02 p.m.
Created at: May 1, 2026, 12:56 a.m.