Triple
T8137069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khreshchatyk Street |
E189997
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Khreshchatyi Yar
Khreshchatyi Yar is the historic ravine area in central Kyiv whose name gave rise to the city’s main thoroughfare, Khreshchatyk Street.
|
E714259
|
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: Khreshchatyi Yar | Statement: [Khreshchatyk Street, namedAfter, Khreshchatyi Yar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khreshchatyi Yar Context triple: [Khreshchatyk Street, namedAfter, Khreshchatyi Yar]
-
A.
Dzyarzhynskaya Hara
Dzyarzhynskaya Hara is the tallest hill in Belarus, known as the country’s highest natural elevation.
-
B.
Yastrebets
Yastrebets is a prominent peak in Bulgaria’s Rila Mountains, known for its ski slopes and panoramic views within the Borovets resort area.
-
C.
Zhmerynka
Zhmerynka is a city in central Ukraine known as an important regional railway junction and administrative center.
-
D.
Ust-Dzheguta
Ust-Dzheguta is a town in the Karachay-Cherkess Republic of southwestern Russia, situated in the North Caucasus region.
-
E.
Vyshny Volochyok
Vyshny Volochyok is a historic town in Tver Oblast, Russia, known as a former key transport hub on the waterway between Moscow and Saint Petersburg.
- 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: Khreshchatyi Yar Triple: [Khreshchatyk Street, namedAfter, Khreshchatyi Yar]
Generated description
Khreshchatyi Yar is the historic ravine area in central Kyiv whose name gave rise to the city’s main thoroughfare, Khreshchatyk Street.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Khreshchatyi Yar Target entity description: Khreshchatyi Yar is the historic ravine area in central Kyiv whose name gave rise to the city’s main thoroughfare, Khreshchatyk Street.
-
A.
Dzyarzhynskaya Hara
Dzyarzhynskaya Hara is the tallest hill in Belarus, known as the country’s highest natural elevation.
-
B.
Yastrebets
Yastrebets is a prominent peak in Bulgaria’s Rila Mountains, known for its ski slopes and panoramic views within the Borovets resort area.
-
C.
Zhmerynka
Zhmerynka is a city in central Ukraine known as an important regional railway junction and administrative center.
-
D.
Ust-Dzheguta
Ust-Dzheguta is a town in the Karachay-Cherkess Republic of southwestern Russia, situated in the North Caucasus region.
-
E.
Vyshny Volochyok
Vyshny Volochyok is a historic town in Tver Oblast, Russia, known as a former key transport hub on the waterway between Moscow and Saint Petersburg.
- 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_69ca82bd9900819099477cdc2eb4244f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb440171d48190afa4a312ab19389c |
completed | March 31, 2026, 3:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc949d9c7c81908efb4880f9250166 |
completed | April 1, 2026, 3:44 a.m. |
| NEDg | Description generation | batch_69cc9605b8248190a621ea934c58913d |
completed | April 1, 2026, 3:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc970cf55c8190abf432ac68d6bbc3 |
completed | April 1, 2026, 3:54 a.m. |
Created at: March 30, 2026, 5:35 p.m.