Triple

T4316509
Position Surface form Disambiguated ID Type / Status
Subject California station (Green Line) E96405 entity
Predicate hasStationCode P1289 FINISHED
Object CAL
CAL is the station code for California station on the Green Line transit system.
 E430438 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: CAL | Statement: [California station (Green Line), hasStationCode, CAL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CAL
Context triple: [California station (Green Line), hasStationCode, CAL]
  • A. CAL
    CAL was the stock ticker symbol for Continental Airlines, a major U.S. airline that later merged with United Airlines.
  • B. CAL
    CAL is the ICAO airline designator used to identify China Airlines in international aviation operations.
  • C. Cal
    Cal is the commonly used short name for the University of California, Berkeley and its associated athletic programs.
  • D. CA
    CA is the IATA airline designator assigned to Air China, the flag carrier of the People's Republic of China.
  • E. CA
    CA is the vehicle registration code used on license plates for the Italian city of Cagliari.
  • 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: CAL
Triple: [California station (Green Line), hasStationCode, CAL]
Generated description
CAL is the station code for California station on the Green Line transit system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CAL
Target entity description: CAL is the station code for California station on the Green Line transit system.
  • A. CAL
    CAL is the ICAO airline designator used to identify China Airlines in international aviation operations.
  • B. CAL
    CAL was the stock ticker symbol for Continental Airlines, a major U.S. airline that later merged with United Airlines.
  • C. Cal
    Cal is the commonly used short name for the University of California, Berkeley and its associated athletic programs.
  • D. CA
    CA is the IATA airline designator assigned to Air China, the flag carrier of the People's Republic of China.
  • E. CA
    CA is the vehicle registration code used on license plates for the Italian city of Cagliari.
  • 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_69b345422aac81909ddbadae437d122e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b350f60dfc819098202b7eb3bbf402 completed March 12, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d085f78481909bb6dd55bf06d9d6 completed March 14, 2026, 9:17 p.m.
NEDg Description generation batch_69b5d0f6d1d48190a3ecd1765043ac58 completed March 14, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_69b5d18381288190948a7a0c42dc8cbf completed March 14, 2026, 9:22 p.m.
Created at: March 12, 2026, 11:12 p.m.