Triple

T4027948
Position Surface form Disambiguated ID Type / Status
Subject Processo Revolucionário em Curso E83637 entity
Predicate alsoKnownAs P39 FINISHED
Object PREC
PREC is the Portuguese acronym for the Processo Revolucionário em Curso, the turbulent revolutionary period following Portugal’s 1974 Carnation Revolution marked by intense political and social transformation.
 E407695 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: PREC | Statement: [Processo Revolucionário em Curso, alsoKnownAs, PREC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PREC
Context triple: [Processo Revolucionário em Curso, alsoKnownAs, PREC]
  • A. Pre
    Pre is the famous nickname of Steve Prefontaine, the iconic American middle- and long-distance runner known for his aggressive racing style and role in popularizing running in the 1970s.
  • B. PAR
    PAR is the IATA city code representing the collective airport system serving Paris, France, including major airports such as Charles de Gaulle and Orly.
  • C. P
    P is the vehicle registration code used on license plates for the Czech city of Plzeň.
  • D. CP
    CP was the IATA airline designator for Canadian Airlines, a former major Canadian carrier.
  • E. CP
    CP is the national railway operator of Portugal, providing passenger and freight train services across the country.
  • 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: PREC
Triple: [Processo Revolucionário em Curso, alsoKnownAs, PREC]
Generated description
PREC is the Portuguese acronym for the Processo Revolucionário em Curso, the turbulent revolutionary period following Portugal’s 1974 Carnation Revolution marked by intense political and social transformation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PREC
Target entity description: PREC is the Portuguese acronym for the Processo Revolucionário em Curso, the turbulent revolutionary period following Portugal’s 1974 Carnation Revolution marked by intense political and social transformation.
  • A. Pre
    Pre is the famous nickname of Steve Prefontaine, the iconic American middle- and long-distance runner known for his aggressive racing style and role in popularizing running in the 1970s.
  • B. PAR
    PAR is the IATA city code representing the collective airport system serving Paris, France, including major airports such as Charles de Gaulle and Orly.
  • C. P
    P is the vehicle registration code used on license plates for the Czech city of Plzeň.
  • D. CP
    CP is the national railway operator of Portugal, providing passenger and freight train services across the country.
  • E. CP
    CP was the IATA airline designator for Canadian Airlines, a former major Canadian carrier.
  • 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_69aed92e29ac819080f7a98b594fec05 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefaeec44881909a6c008eeae204df completed March 9, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b556325c48819099d4cb5c2049d7e7 completed March 14, 2026, 12:36 p.m.
NEDg Description generation batch_69b556bd17f481909647a10398025f3e completed March 14, 2026, 12:38 p.m.
NED2 Entity disambiguation (via description) batch_69b55733159481908d5a427a57bef9a3 completed March 14, 2026, 12:40 p.m.
Created at: March 9, 2026, 3:36 p.m.