Triple

T35789129
Position Surface form Disambiguated ID Type / Status
Subject Fly Leaves E1034640 entity
Predicate hasPoem P21160 FINISHED
Object The Ode to the Great Unknown
The Ode to the Great Unknown is a poem from the 19th-century poetry collection "Fly Leaves" by C. S. Calverley, reflecting his characteristic blend of wit and reflective lyricism.
 E2157013 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 Ode to the Great Unknown | Statement: [Fly Leaves, hasPoem, The Ode to the Great Unknown]
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 Ode to the Great Unknown
Triple: [Fly Leaves, hasPoem, The Ode to the Great Unknown]
Generated description
The Ode to the Great Unknown is a poem from the 19th-century poetry collection "Fly Leaves" by C. S. Calverley, reflecting his characteristic blend of wit and reflective lyricism.

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_69f76e1575908190aaa306d843b41c14 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a22cd75c81909c3a721b69f8b9a5 completed May 3, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38915ffd788190bb39bdb5feeb5405 completed June 22, 2026, 1:35 a.m.
NEDg Description generation batch_6a3893ef4c9081909bb33191ca613ad2 completed June 22, 2026, 1:46 a.m.
NED2 Entity disambiguation (via description) batch_6a3894639648819098072e40ca4d0254 completed June 22, 2026, 1:48 a.m.
Created at: May 3, 2026, 4:06 p.m.