Triple

T2752661
Position Surface form Disambiguated ID Type / Status
Subject TeX E61023 entity
Predicate influenced P9 FINISHED
Object SILE
SILE is a modern typesetting system and document processor designed as a more flexible, programmable successor to traditional TeX-based workflows.
 E295374 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: SILE | Statement: [TeX, influenced, SILE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SILE
Context triple: [TeX, influenced, SILE]
  • A. SILJU
    SILJU is the UN/LOCODE designation for the city and transport hub of Ljubljana, the capital of Slovenia.
  • B. Silay
    Silay is a heritage-rich city in the Philippine province of Negros Occidental, known for its well-preserved ancestral houses and cultural history.
  • C. Sisebut
    Sisebut was an early 7th-century king of the Visigoths known for his military campaigns against the Byzantines in Hispania and his promotion of Christianity, including forced conversions of Jews.
  • D. Sis
    Sis was the medieval capital city of the Armenian Kingdom of Cilicia, serving as its political and cultural center.
  • E. SIF
    SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
  • 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: SILE
Triple: [TeX, influenced, SILE]
Generated description
SILE is a modern typesetting system and document processor designed as a more flexible, programmable successor to traditional TeX-based workflows.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SILE
Target entity description: SILE is a modern typesetting system and document processor designed as a more flexible, programmable successor to traditional TeX-based workflows.
  • A. SILJU
    SILJU is the UN/LOCODE designation for the city and transport hub of Ljubljana, the capital of Slovenia.
  • B. Silay
    Silay is a heritage-rich city in the Philippine province of Negros Occidental, known for its well-preserved ancestral houses and cultural history.
  • C. Sisebut
    Sisebut was an early 7th-century king of the Visigoths known for his military campaigns against the Byzantines in Hispania and his promotion of Christianity, including forced conversions of Jews.
  • D. Sis
    Sis was the medieval capital city of the Armenian Kingdom of Cilicia, serving as its political and cultural center.
  • E. SIF
    SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
  • 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_69ab4b7a85bc819094a349b84beb1f2c completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb6ed9c08190824d1866e198ef80 completed March 7, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbdb43d481909bf4e61840979c0a completed March 10, 2026, 6:36 a.m.
NEDg Description generation batch_69afbc758cc48190a96f80a850316ce3 completed March 10, 2026, 6:38 a.m.
NED2 Entity disambiguation (via description) batch_69afbd7be9088190a19bed27249e95c4 completed March 10, 2026, 6:43 a.m.
Created at: March 6, 2026, 9:56 p.m.