Triple

T37618145
Position Surface form Disambiguated ID Type / Status
Subject Jim Shepard E935986 entity
Predicate notableWork P4 FINISHED
Object Like You’d Understand, Anyway
Like You’d Understand, Anyway is a critically acclaimed short story collection by American writer Jim Shepard, known for its historically and scientifically grounded tales that explore extreme situations and moral complexity.
 E2236021 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: Like You’d Understand, Anyway | Statement: [Jim Shepard, notableWork, Like You’d Understand, Anyway]
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: Like You’d Understand, Anyway
Triple: [Jim Shepard, notableWork, Like You’d Understand, Anyway]
Generated description
Like You’d Understand, Anyway is a critically acclaimed short story collection by American writer Jim Shepard, known for its historically and scientifically grounded tales that explore extreme situations and moral complexity.

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_69f76ed16b748190ad6add183b1be688 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba92ed94081909b4995680499707b completed May 6, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40afe8ecf08190b89798e6d290a6b3 completed June 28, 2026, 5:23 a.m.
NEDg Description generation batch_6a40b16a68c08190ae4204e7cf4cdf68 completed June 28, 2026, 5:30 a.m.
NED2 Entity disambiguation (via description) batch_6a40b204c12c819085dadeffc57aa2d4 completed June 28, 2026, 5:32 a.m.
Created at: May 3, 2026, 4:18 p.m.