Triple

T16310601
Position Surface form Disambiguated ID Type / Status
Subject Final Space E396043 entity
Predicate mainCharacter P1183 FINISHED
Object KVN
KVN is the annoyingly cheerful and often incompetent robot companion in the animated sci-fi series "Final Space."
E1206340 NE FINISHED

How this triple was built (4 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: KVN | Statement: [Final Space, mainCharacter, KVN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KVN
Context triple: [Final Space, mainCharacter, KVN]
  • A. Petrovskiy
    Petrovskiy is a Slavic surname derived from the given name Petro, commonly indicating familial or ancestral association with someone named Petro.
  • B. Knv
    Knv is the station code for Knivsta railway station in Sweden.
  • C. Ershevka
    Ershevka is a rural locality in Kaluga Oblast, Russia.
  • D. Zvezdochka
    Zvezdochka is a major Russian shipyard and naval repair facility located in Severodvinsk, known especially for servicing and modernizing submarines.
  • E. Boryslav Laughs
    Boryslav Laughs is a social and psychological novel by Ukrainian writer Ivan Franko that portrays the harsh lives of oil field workers and critiques capitalist exploitation in the Boryslav region.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: KVN
Triple: [Final Space, mainCharacter, KVN]
Generated description
KVN is the annoyingly cheerful and often incompetent robot companion in the animated sci-fi series "Final Space."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: KVN
Target entity description: KVN is the annoyingly cheerful and often incompetent robot companion in the animated sci-fi series "Final Space."
  • A. Petrovskiy
    Petrovskiy is a Slavic surname derived from the given name Petro, commonly indicating familial or ancestral association with someone named Petro.
  • B. Knv
    Knv is the station code for Knivsta railway station in Sweden.
  • C. Ershevka
    Ershevka is a rural locality in Kaluga Oblast, Russia.
  • D. Zvezdochka
    Zvezdochka is a major Russian shipyard and naval repair facility located in Severodvinsk, known especially for servicing and modernizing submarines.
  • E. Boryslav Laughs
    Boryslav Laughs is a social and psychological novel by Ukrainian writer Ivan Franko that portrays the harsh lives of oil field workers and critiques capitalist exploitation in the Boryslav region.
  • F. None of above. chosen

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_69d87f23bb088190a16fbb91a1957ea5 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e288da27f88190aa241e3addf9cd7f completed April 17, 2026, 7:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001fa6ceb48190b937a15b94fd3cfa completed May 10, 2026, 6:03 a.m.
NEDg Description generation batch_6a00219696dc8190bcce66c1eeb07561 completed May 10, 2026, 6:11 a.m.
NED2 Entity disambiguation (via description) batch_6a002221fe7c819083c8ede5e63b0908 completed May 10, 2026, 6:13 a.m.
Created at: April 10, 2026, 5:06 a.m.