Triple
T2753900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zamość |
E61054
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Lutsk |
E6073
|
NE FINISHED |
How this triple was built (2 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: Lutsk | Statement: [Zamość, twinTown, Lutsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lutsk Context triple: [Zamość, twinTown, Lutsk]
-
A.
Lutsk
chosen
Lutsk is a historic city in northwestern Ukraine, known as the administrative center of Volyn Oblast and one of the region’s oldest cultural and economic hubs.
-
B.
Drohobych
Drohobych is a historic city in western Ukraine known for its medieval architecture, salt production heritage, and association with writer and artist Bruno Schulz.
-
C.
Ternopil
Ternopil is a city in western Ukraine known as a regional cultural and economic center with a historic old town and a picturesque lakeside setting.
-
D.
Rivne
Rivne is a city in western Ukraine that serves as an important regional administrative, economic, and cultural center.
-
E.
Cherkasy
Cherkasy is a city in central Ukraine located on the banks of the Dnieper River and serving as an important regional industrial and cultural center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb7073d081909da84b21015972f2 |
completed | March 7, 2026, 8:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b367e000dc8190baba64c6e8ccf308 |
completed | March 13, 2026, 1:26 a.m. |
Created at: March 6, 2026, 9:56 p.m.