Triple

T30605754
Position Surface form Disambiguated ID Type / Status
Subject Porto Corsa E779037 entity
Predicate raceCircuitName P170772 FINISHED
Object Porto Corsa circuit
The Porto Corsa circuit is a fictional Italian coastal racetrack featured in Pixar's animated film "Cars 2," known for its scenic Mediterranean setting and high-speed racing.
 E1926629 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: Porto Corsa circuit | Statement: [Porto Corsa, raceCircuitName, Porto Corsa circuit]
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: Porto Corsa circuit
Triple: [Porto Corsa, raceCircuitName, Porto Corsa circuit]
Generated description
The Porto Corsa circuit is a fictional Italian coastal racetrack featured in Pixar's animated film "Cars 2," known for its scenic Mediterranean setting and high-speed racing.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: raceCircuitName
Context triple: [Porto Corsa, raceCircuitName, Porto Corsa circuit]
  • A. raceWinCircuit
    Indicates that an entity wins a race that takes place on a specific circuit.
  • B. raceName
    Indicates the specific race or competition designation associated with an entity or event.
  • C. racingSeries
    Indicates that one entity is a racing series in which the other entity (such as a race, team, or driver) participates or to which it belongs.
  • D. raceComponent
    Indicates that one entity is a constituent part, segment, or stage within a larger race or racing event involving another entity.
  • E. hasMotorRacingCircuit
    Indicates that a location or entity possesses, contains, or is the site of a motor racing circuit.
  • F. None of above. chosen

Provenance (7 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_69f224a21fc08190abd9d8dd9eb6bb4c completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f695f9fe7c819084322bf6cdc70a13 completed May 3, 2026, 12:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2870e0ad6881908a4cc9c68f99e23b completed June 9, 2026, 8 p.m.
NEDg Description generation batch_6a28727d4a1c8190a8ea35db2ff730c2 completed June 9, 2026, 8:07 p.m.
NED2 Entity disambiguation (via description) batch_6a2877b1f8108190a24d8cbdab246c20 completed June 9, 2026, 8:29 p.m.
PD Predicate disambiguation batch_69f690ed5d008190831cf8e44cce28af completed May 3, 2026, 12:03 a.m.
PDg Predicate description generation batch_69f695385a2881908cc28ef97fffc867 completed May 3, 2026, 12:22 a.m.
Created at: April 29, 2026, 8:25 p.m.