Triple
T11143204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A4 motorway |
E263606
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Rzeszów |
E220683
|
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: Rzeszów | Statement: [A4 motorway, passesNear, Rzeszów]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rzeszów Context triple: [A4 motorway, passesNear, Rzeszów]
-
A.
Rzeszów
chosen
Rzeszów is a major city in southeastern Poland known as an important economic, academic, and cultural center of the region.
-
B.
Przemyśl
Przemyśl is a historic city in southeastern Poland near the Ukrainian border, known for its strategic location, multicultural heritage, and well-preserved fortifications.
-
C.
Hrubieszów
Hrubieszów is a historic town in eastern Poland near the Ukrainian border, known for its multicultural heritage and location in the Lublin region.
-
D.
Tarnów
Tarnów is a historic city in southern Poland known for its well-preserved Old Town, Renaissance architecture, and cultural heritage.
-
E.
Bielsko-Biała
Bielsko-Biała is a city in southern Poland at the foot of the Beskid Mountains, known as a regional industrial and cultural center formed from the historic towns of Bielsko and Biała.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8623158819096ad1678fa9e72bb |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5255f7730819087dc4b10565e321d |
completed | April 19, 2026, 6:56 p.m. |
Created at: April 8, 2026, 9:28 p.m.