Triple

T28667948
Position Surface form Disambiguated ID Type / Status
Subject Frank Belknap Long E725631 entity
Predicate notableWork P4 FINISHED
Object The Dark Beasts
The Dark Beasts is a horror story by American writer Frank Belknap Long, known for its eerie atmosphere and contribution to early 20th-century weird fiction.
 E1827714 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 Dark Beasts | Statement: [Frank Belknap Long, notableWork, The Dark Beasts]
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 Dark Beasts
Triple: [Frank Belknap Long, notableWork, The Dark Beasts]
Generated description
The Dark Beasts is a horror story by American writer Frank Belknap Long, known for its eerie atmosphere and contribution to early 20th-century weird 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_69f01d85be388190b669a0e401e2f2c4 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f655a606c88190827a1439523777f6 completed May 2, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cc3a1bbc88190a92584faed3748d5 completed May 31, 2026, 11:26 p.m.
NEDg Description generation batch_6a1cc4d77b08819093f087eef76162df completed May 31, 2026, 11:31 p.m.
NED2 Entity disambiguation (via description) batch_6a1cc55723b08190a4cc5cb40e0d46ea completed May 31, 2026, 11:33 p.m.
Created at: April 28, 2026, 5:02 a.m.