Triple

T1236005
Position Surface form Disambiguated ID Type / Status
Subject Cercanías Madrid E26548 entity
Predicate line P1293 FINISHED
Object C-3a
C-3a is a commuter rail line within the Cercanías Madrid network serving suburban areas around Spain’s capital.
 E140898 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: C-3a | Statement: [Cercanías Madrid, line, C-3a]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: C-3a
Context triple: [Cercanías Madrid, line, C-3a]
  • A. C.205
    C.205 is the Italian Air Force designation for the Macchi C.205 Veltro, a World War II-era single-seat fighter aircraft.
  • B. A3C
    A3C (Asynchronous Advantage Actor-Critic) is a reinforcement learning algorithm that trains multiple parallel agents to learn policies and value functions efficiently using asynchronous gradient updates.
  • C. TCA
    TCA is the commonly used abbreviation for the Technical Cooperation Administration, a former U.S. government agency responsible for administering foreign aid and technical assistance programs.
  • D. CUB
    CUB is the three-letter ISO 3166-1 alpha-3 country code assigned to Cuba for international standardization and identification purposes.
  • E. CUB
    CUB is the ICAO airline designator assigned to Cubana de Aviación, the national flag carrier of Cuba.
  • 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: C-3a
Triple: [Cercanías Madrid, line, C-3a]
Generated description
C-3a is a commuter rail line within the Cercanías Madrid network serving suburban areas around Spain’s capital.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: C-3a
Target entity description: C-3a is a commuter rail line within the Cercanías Madrid network serving suburban areas around Spain’s capital.
  • A. C.205
    C.205 is the Italian Air Force designation for the Macchi C.205 Veltro, a World War II-era single-seat fighter aircraft.
  • B. A3C
    A3C (Asynchronous Advantage Actor-Critic) is a reinforcement learning algorithm that trains multiple parallel agents to learn policies and value functions efficiently using asynchronous gradient updates.
  • C. TCA
    TCA is the commonly used abbreviation for the Technical Cooperation Administration, a former U.S. government agency responsible for administering foreign aid and technical assistance programs.
  • D. CUB
    CUB is the three-letter ISO 3166-1 alpha-3 country code assigned to Cuba for international standardization and identification purposes.
  • E. CUB
    CUB is the ICAO airline designator assigned to Cubana de Aviación, the national flag carrier of Cuba.
  • 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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf17e0bc8190a066561e6b629fc0 completed March 1, 2026, 10:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8a18b0f48190adb5b2c1e2a1019a completed March 7, 2026, 8:27 p.m.
NEDg Description generation batch_69ac8aa863a08190b21071a4ed2e74b9 completed March 7, 2026, 8:29 p.m.
NED2 Entity disambiguation (via description) batch_69ac8b72cb6c8190984bd3d4b0d54262 completed March 7, 2026, 8:32 p.m.
Created at: March 1, 2026, 7:47 p.m.