Triple

T38668032
Position Surface form Disambiguated ID Type / Status
Subject Mario Bava E940508 entity
Predicate notableWork P4 FINISHED
Object Planet of the Vampires
Planet of the Vampires is a 1965 Italian science fiction–horror film, directed by Mario Bava, known for its atmospheric visuals and influential blend of gothic and space terror.
E2280853 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: Planet of the Vampires | Statement: [Mario Bava, notableWork, Planet of the Vampires]
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: Planet of the Vampires
Triple: [Mario Bava, notableWork, Planet of the Vampires]
Generated description
Planet of the Vampires is a 1965 Italian science fiction–horror film, directed by Mario Bava, known for its atmospheric visuals and influential blend of gothic and space terror.

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_69f76edfde348190bf6529d9f49ecd62 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcdc101ed88190988619025c9350c2 completed May 7, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41fd6b97688190897da0570f428cb6 completed June 29, 2026, 5:06 a.m.
NEDg Description generation batch_6a4200f24c4081908af3a6cda3fff8a8 completed June 29, 2026, 5:21 a.m.
NED2 Entity disambiguation (via description) batch_6a4201588dd48190a238cf8e411a1fce completed June 29, 2026, 5:23 a.m.
Created at: May 3, 2026, 4:33 p.m.