Triple

T13485067
Position Surface form Disambiguated ID Type / Status
Subject Santa Isabel station E318474 entity
Predicate hasStationCode P1289 FINISHED
Object SI
SI is the station code used to identify Santa Isabel station within the railway network.
 E1042059 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: SI | Statement: [Santa Isabel station, hasStationCode, SI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SI
Context triple: [Santa Isabel station, hasStationCode, SI]
  • A. SI
    SI is the vehicle registration code used on license plates for the German city of Siegen.
  • B. SI
    SI is the abbreviation for Skeptical Inquirer, a magazine devoted to scientific skepticism, critical thinking, and the investigation of extraordinary claims.
  • C. SI
    SI is the globally accepted metric-based system of measurement used in science, industry, and everyday life.
  • D. SI
    SI is the post-nominal abbreviation used to denote recipients of Pakistan’s Sitara-e-Imtiaz, one of the country’s highest civilian honors.
  • E. Si
    Si is one of the mischievous Siamese cats from Disney’s animated film "Lady and the Tramp," known for causing trouble with her twin, Am.
  • 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: SI
Triple: [Santa Isabel station, hasStationCode, SI]
Generated description
SI is the station code used to identify Santa Isabel station within the railway network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SI
Target entity description: SI is the station code used to identify Santa Isabel station within the railway network.
  • A. SI
    SI is the abbreviation for Skeptical Inquirer, a magazine devoted to scientific skepticism, critical thinking, and the investigation of extraordinary claims.
  • B. SI
    SI is the globally accepted metric-based system of measurement used in science, industry, and everyday life.
  • C. SI
    SI is the post-nominal abbreviation used to denote recipients of Pakistan’s Sitara-e-Imtiaz, one of the country’s highest civilian honors.
  • D. SI
    SI is the vehicle registration code used on license plates for the German city of Siegen.
  • E. Si
    Si is one of the mischievous Siamese cats from Disney’s animated film "Lady and the Tramp," known for causing trouble with her twin, Am.
  • 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf3a15b48190b63fb59e926a97ae completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7463715dc8190a70a17b3ea661006 completed May 3, 2026, 12:57 p.m.
NEDg Description generation batch_69f74bac36e081909dae786e14883e3c completed May 3, 2026, 1:20 p.m.
NED2 Entity disambiguation (via description) batch_69f74c5195188190bad111b301713426 completed May 3, 2026, 1:23 p.m.
Created at: April 9, 2026, 9:42 p.m.