Triple

T4340931
Position Surface form Disambiguated ID Type / Status
Subject Filmstaden Sergel E97576 entity
Predicate formerName P65 FINISHED
Object SF Sergel
SF Sergel was a major central Stockholm cinema complex, later rebranded as Filmstaden Sergel, known for showing mainstream and blockbuster films.
 E432142 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: SF Sergel | Statement: [Filmstaden Sergel, formerName, SF Sergel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SF Sergel
Context triple: [Filmstaden Sergel, formerName, SF Sergel]
  • A. Sven
    Sven is the lovable reindeer companion in Disney's animated film "Frozen," known for his close bond with Kristoff and his expressive, dog-like personality.
  • B. Senger
    Senger is a variant form of the surname Singer, commonly found in German-speaking regions.
  • C. Serge
    Serge is a masculine given name of French origin, commonly used in Francophone countries and derived from the Latin name Sergius.
  • D. Sergy
    Sergy is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • E. Severin "Sere" Iversen
    Severin "Sere" Iversen is a songwriter best known for co-writing Alicia Keys’ track "Wait Til You See My Smile."
  • 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: SF Sergel
Triple: [Filmstaden Sergel, formerName, SF Sergel]
Generated description
SF Sergel was a major central Stockholm cinema complex, later rebranded as Filmstaden Sergel, known for showing mainstream and blockbuster films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SF Sergel
Target entity description: SF Sergel was a major central Stockholm cinema complex, later rebranded as Filmstaden Sergel, known for showing mainstream and blockbuster films.
  • A. Sven
    Sven is the lovable reindeer companion in Disney's animated film "Frozen," known for his close bond with Kristoff and his expressive, dog-like personality.
  • B. Senger
    Senger is a variant form of the surname Singer, commonly found in German-speaking regions.
  • C. Serge
    Serge is a masculine given name of French origin, commonly used in Francophone countries and derived from the Latin name Sergius.
  • D. Sergy
    Sergy is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • E. Severin "Sere" Iversen
    Severin "Sere" Iversen is a songwriter best known for co-writing Alicia Keys’ track "Wait Til You See My Smile."
  • 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_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35170a6648190a15ffb21640ee478 completed March 12, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d0b301188190af8514a675aebb5f completed March 14, 2026, 9:18 p.m.
NEDg Description generation batch_69b5d137271c8190a2d66fb47eb10d93 completed March 14, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_69b5d4e5e24c8190980bc545ca0d339d completed March 14, 2026, 9:36 p.m.
Created at: March 12, 2026, 11:14 p.m.