Triple

T29766070
Position Surface form Disambiguated ID Type / Status
Subject The Body Lovers E753910 entity
Predicate hasFictionalUniverse P3758 FINISHED
Object Mike Hammer universe
The Mike Hammer universe is the hard-boiled, noir crime-fiction setting centered on Mickey Spillane’s tough private detective Mike Hammer, featuring gritty urban mysteries, violence, and moral ambiguity.
E206884 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: Mike Hammer universe | Statement: [The Body Lovers, hasFictionalUniverse, Mike Hammer universe]
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: Mike Hammer universe
Triple: [The Body Lovers, hasFictionalUniverse, Mike Hammer universe]
Generated description
The Mike Hammer universe is the hard-boiled, noir crime-fiction setting centered on Mickey Spillane’s tough private detective Mike Hammer, featuring gritty urban mysteries, violence, and moral ambiguity.

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_69f0ef827ff88190ade56e0b0846b713 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f6745c64e08190b36a80dbbedb1db6 completed May 2, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27320f78a88190a5ce8abe5da5f7cd completed June 8, 2026, 9:20 p.m.
NEDg Description generation batch_6a2734bcb1ac819097f57e24df7f092c completed June 8, 2026, 9:31 p.m.
NED2 Entity disambiguation (via description) batch_6a27354a6e1c8190a0f01c78ef8c10c6 completed June 8, 2026, 9:34 p.m.
Created at: April 28, 2026, 8:38 p.m.