Triple

T6969400
Position Surface form Disambiguated ID Type / Status
Subject Sri Venkateswara Creations E161564 entity
Predicate alsoKnownAs P39 FINISHED
Object SVC
SVC is the commonly used abbreviation for Sri Venkateswara Creations, a prominent Indian film production company known for producing Telugu-language movies.
E632310 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: SVC | Statement: [Sri Venkateswara Creations, alsoKnownAs, SVC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SVC
Context triple: [Sri Venkateswara Creations, alsoKnownAs, SVC]
  • A. SVC
    SVC is scikit-learn’s implementation of a Support Vector Machine classifier used for supervised learning tasks such as binary and multiclass classification.
  • B. SVCN
    SVCN is the ICAO airport code for Canaima airstrip, a small airport serving the Canaima National Park region in Venezuela.
  • C. SVR
    SVR is the ICAO airline designator assigned to Ural Airlines, a Russian commercial air carrier.
  • D. SVR
    SVR is Russia’s primary foreign intelligence service, which succeeded the Soviet-era KGB’s external intelligence functions after the USSR’s dissolution.
  • E. SVR
    SVR is the set of post-nominal letters used to denote recipients of the Order of the White Rose of Finland.
  • 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: SVC
Triple: [Sri Venkateswara Creations, alsoKnownAs, SVC]
Generated description
SVC is the commonly used abbreviation for Sri Venkateswara Creations, a prominent Indian film production company known for producing Telugu-language movies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: SVC
Target entity description: SVC is the commonly used abbreviation for Sri Venkateswara Creations, a prominent Indian film production company known for producing Telugu-language movies.
  • A. SVC
    SVC is scikit-learn’s implementation of a Support Vector Machine classifier used for supervised learning tasks such as binary and multiclass classification.
  • B. SVCN
    SVCN is the ICAO airport code for Canaima airstrip, a small airport serving the Canaima National Park region in Venezuela.
  • C. SVR
    SVR is the ICAO airline designator assigned to Ural Airlines, a Russian commercial air carrier.
  • D. SVR
    SVR is the set of post-nominal letters used to denote recipients of the Order of the White Rose of Finland.
  • E. SVR
    SVR is Russia’s primary foreign intelligence service, which succeeded the Soviet-era KGB’s external intelligence functions after the USSR’s dissolution.
  • 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_69c68853cff881908439d488924a8283 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db1649288190a52c7dab57b3c7dc completed March 27, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7619ada248190941ddf3b13cf3a74 completed March 28, 2026, 5:05 a.m.
NEDg Description generation batch_69c76251647c8190b0c30d4aa8301f8c completed March 28, 2026, 5:08 a.m.
NED2 Entity disambiguation (via description) batch_69c762d1be208190ae5831c2a5e5655c completed March 28, 2026, 5:10 a.m.
Created at: March 27, 2026, 2:30 p.m.