Triple

T29245739
Position Surface form Disambiguated ID Type / Status
Subject Portorosso Cup triathlon E741436 entity
Predicate swimmingSegmentLocation P131303 FINISHED
Object Portorosso harbor
Portorosso harbor is the seaside port of the fictional Italian town in Pixar's film "Luca," serving as a central setting for the story's events and activities.
 E1860827 NE FINISHED

How this triple was built (3 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: Portorosso harbor | Statement: [Portorosso Cup triathlon, swimmingSegmentLocation, Portorosso harbor]
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: Portorosso harbor
Triple: [Portorosso Cup triathlon, swimmingSegmentLocation, Portorosso harbor]
Generated description
Portorosso harbor is the seaside port of the fictional Italian town in Pixar's film "Luca," serving as a central setting for the story's events and activities.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: swimmingSegmentLocation
Context triple: [Portorosso Cup triathlon, swimmingSegmentLocation, Portorosso harbor]
  • A. swimmingZone chosen
    Indicates a designated area where swimming is permitted or intended to take place.
  • B. swimmingLevel
    Indicates the degree of proficiency or skill an entity has in swimming.
  • C. distancePerSwimmer
    Indicates the amount of distance associated with or covered by each individual swimmer.
  • D. swimmingType
    Indicates the manner or style in which an entity performs the action of swimming.
  • E. swimCourse
    Indicates that an entity is a course or path specifically designated or used for swimming.
  • F. None of above.

Provenance (6 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_69f0911eba2c8190b07cd2fdf91422c9 completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f66489459c8190aa343cb2b8af1300 completed May 2, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25a84dea7481909f4e5cd9f860b182 completed June 7, 2026, 5:20 p.m.
NEDg Description generation batch_6a25b42eb72c81908feb64f5c32145ea completed June 7, 2026, 6:10 p.m.
NED2 Entity disambiguation (via description) batch_6a25b44a65f48190a1f872ebc1c2bf9d completed June 7, 2026, 6:11 p.m.
PD Predicate disambiguation batch_69f65c24f8b48190af81b575f3c15be5 completed May 2, 2026, 8:18 p.m.
Created at: April 28, 2026, 12:32 p.m.