Triple

T26571561
Position Surface form Disambiguated ID Type / Status
Subject Ring Lardner E666839 entity
Predicate notableWork P4 FINISHED
Object Some Like Them Cold
Some Like Them Cold is a humorous epistolary short story by American writer Ring Lardner that satirizes romance and social pretensions through a series of letters between its main characters.
 E1733073 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: Some Like Them Cold | Statement: [Ring Lardner, notableWork, Some Like Them Cold]
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: Some Like Them Cold
Triple: [Ring Lardner, notableWork, Some Like Them Cold]
Generated description
Some Like Them Cold is a humorous epistolary short story by American writer Ring Lardner that satirizes romance and social pretensions through a series of letters between its main characters.

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_69ee9cfa21c081909e4e36e087debfc6 completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f614a3e3b88190935c9fe7dbc71f54 completed May 2, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c82cb5ec8190b5016f40ebe81029 completed May 23, 2026, 3:30 p.m.
NEDg Description generation batch_6a11c91aa6888190b17f656a39eefd1e completed May 23, 2026, 3:34 p.m.
NED2 Entity disambiguation (via description) batch_6a11ca68b0488190851b0634a0c784bd completed May 23, 2026, 3:40 p.m.
Created at: April 27, 2026, 1:58 a.m.