Triple
T4646063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AGAT |
E101774
|
entity |
| Predicate | garrison |
P75
|
FINISHED |
| Object | Gliwice |
E333563
|
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: Gliwice | Statement: [AGAT, garrison, Gliwice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gliwice Context triple: [AGAT, garrison, Gliwice]
-
A.
Gliwice
chosen
Gliwice is a historic industrial and academic city in southern Poland’s Silesian region, known for its engineering university and the landmark Gliwice Radio Tower.
-
B.
Chorzów
Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
-
C.
Katowice
Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
-
D.
Dąbrowa Górnicza
Dąbrowa Górnicza is an industrial city in southern Poland’s Silesian Voivodeship, known for its heavy industry, mining heritage, and proximity to the unique Błędów Desert.
-
E.
Tychy
Tychy is a city in the Silesian region of southern Poland, known for its brewing industry and role as a planned industrial 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_69bd43d3bc7c81908f81fcf380476b0f |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd623815288190b21cf59a3786363d |
completed | March 20, 2026, 3:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c95675f24c81909f9c14e29a79c157 |
completed | March 29, 2026, 4:42 p.m. |
Created at: March 20, 2026, 1:14 p.m.