Triple

T32157799
Position Surface form Disambiguated ID Type / Status
Subject American Depression-era literature canon E821344 entity
Predicate hasWork P6260 FINISHED
Object Now in November
"Now in November" is a 1934 novel by Josephine Johnson that portrays the struggles of a farm family during the Great Depression and won the Pulitzer Prize for Fiction.
 E1996331 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: Now in November | Statement: [American Depression-era literature canon, hasWork, Now in November]
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: Now in November
Triple: [American Depression-era literature canon, hasWork, Now in November]
Generated description
"Now in November" is a 1934 novel by Josephine Johnson that portrays the struggles of a farm family during the Great Depression and won the Pulitzer Prize for Fiction.

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_69f34905e098819082191a6922a6d607 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b9efb60881908feca779d10fef5b completed May 3, 2026, 2:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0bce6ab08190af1cd09f8935dfa6 completed June 14, 2026, 8:15 p.m.
NEDg Description generation batch_6a2f0c47380881909610ef39ac0c5a79 completed June 14, 2026, 8:17 p.m.
NED2 Entity disambiguation (via description) batch_6a2f2eee843881909b1b90c96ec496fe completed June 14, 2026, 10:45 p.m.
Created at: May 1, 2026, 12:32 a.m.