Triple

T4578125
Position Surface form Disambiguated ID Type / Status
Subject Social Code Book XI E101788 entity
Predicate abbreviation P43 FINISHED
Object SGB XI
SGB XI is the German Social Code Book that regulates the country’s statutory long-term care insurance system.
E453553 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: SGB XI | Statement: [Social Code Book XI, abbreviation, SGB XI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SGB XI
Context triple: [Social Code Book XI, abbreviation, SGB XI]
  • A. SIPG
    SIPG is the state-owned operator and managing company of the Port of Shanghai, one of the world’s busiest container ports.
  • B. Club Sportif Sfaxien
    Club Sportif Sfaxien is a prominent Tunisian football club based in Sfax, known for its strong domestic record and intense rivalry with Espérance Sportive de Tunis.
  • C. Club 152
    Club 152 is a popular multi-level bar and live music venue on Memphis’s historic Beale Street, known for its energetic nightlife and performances.
  • D. Divisione Nazionale
    Divisione Nazionale was the former top-tier Italian football league that preceded the modern Serie A format.
  • E. Melgar
    Melgar is a popular tourist town in Colombia known for its warm climate, water parks, and proximity to major cities like Bogotá.
  • 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: SGB XI
Triple: [Social Code Book XI, abbreviation, SGB XI]
Generated description
SGB XI is the German Social Code Book that regulates the country’s statutory long-term care insurance system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: SGB XI
Target entity description: SGB XI is the German Social Code Book that regulates the country’s statutory long-term care insurance system.
  • A. SIPG
    SIPG is the state-owned operator and managing company of the Port of Shanghai, one of the world’s busiest container ports.
  • B. Club Sportif Sfaxien
    Club Sportif Sfaxien is a prominent Tunisian football club based in Sfax, known for its strong domestic record and intense rivalry with Espérance Sportive de Tunis.
  • C. Club 152
    Club 152 is a popular multi-level bar and live music venue on Memphis’s historic Beale Street, known for its energetic nightlife and performances.
  • D. Divisione Nazionale
    Divisione Nazionale was the former top-tier Italian football league that preceded the modern Serie A format.
  • E. Melgar
    Melgar is a popular tourist town in Colombia known for its warm climate, water parks, and proximity to major cities like Bogotá.
  • 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_69bd43d4ce208190b53158c882b222e3 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd58e2a1808190be4582d5b3003d6c completed March 20, 2026, 2:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd3ee510481909d481b157bd0b2bd completed March 20, 2026, 11:10 p.m.
NEDg Description generation batch_69bdd5a85488819092a4a7cc4f58a425 completed March 20, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_69bdd63370088190adca99373f83374f completed March 20, 2026, 11:20 p.m.
Created at: March 20, 2026, 1:10 p.m.