Triple
T8907977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kharkiv Metro |
E212108
|
entity |
| Predicate | hasInterchangeStation |
P2413
|
FINISHED |
| Object |
Sportyvna
Sportyvna is a metro station in Kharkiv, Ukraine, serving as a key interchange point within the Kharkiv Metro system.
|
E765651
|
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: Sportyvna | Statement: [Kharkiv Metro, hasInterchangeStation, Sportyvna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sportyvna Context triple: [Kharkiv Metro, hasInterchangeStation, Sportyvna]
-
A.
Sportiva
Sportiva is a tire brand owned by Continental AG, offering budget-friendly tires for everyday driving needs.
-
B.
Sportwagon
Sportwagon is the estate (station wagon) variant of the Alfa Romeo 156, offering increased practicality while retaining the model’s sporty character.
-
C.
Carrera
Carrera is a renowned line of luxury sports watches produced by the Swiss watchmaker TAG Heuer, known for its racing-inspired design and chronograph functionality.
-
D.
Carrera
Carrera is a Spanish-language surname of Basque origin borne by various notable figures in Hispanic history and culture.
-
E.
Carrera
Carrera is a model designation used by Porsche for high-performance variants of its 911 sports car, known for their speed, handling, and iconic design.
- 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: Sportyvna Triple: [Kharkiv Metro, hasInterchangeStation, Sportyvna]
Generated description
Sportyvna is a metro station in Kharkiv, Ukraine, serving as a key interchange point within the Kharkiv Metro system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sportyvna Target entity description: Sportyvna is a metro station in Kharkiv, Ukraine, serving as a key interchange point within the Kharkiv Metro system.
-
A.
Sportiva
Sportiva is a tire brand owned by Continental AG, offering budget-friendly tires for everyday driving needs.
-
B.
Sportwagon
Sportwagon is the estate (station wagon) variant of the Alfa Romeo 156, offering increased practicality while retaining the model’s sporty character.
-
C.
Carrera
Carrera is a renowned line of luxury sports watches produced by the Swiss watchmaker TAG Heuer, known for its racing-inspired design and chronograph functionality.
-
D.
Carrera
Carrera is a Spanish-language surname of Basque origin borne by various notable figures in Hispanic history and culture.
-
E.
Carrera
Carrera is a model designation used by Porsche for high-performance variants of its 911 sports car, known for their speed, handling, and iconic design.
- 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_69ca839255248190b43984294abd92ae |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc64c6a87c81909331a39619f913c0 |
completed | April 1, 2026, 12:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba31fc148190a8dbe378694dcc32 |
completed | April 3, 2026, 1:01 p.m. |
| NEDg | Description generation | batch_69cfbabf33a08190a18d13b9078c00e2 |
completed | April 3, 2026, 1:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfbba71a948190afc03a1df9e5777c |
completed | April 3, 2026, 1:07 p.m. |
Created at: March 30, 2026, 6:55 p.m.