Triple
T21385462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mielec |
E527482
|
entity |
| Predicate | hasIndustrialPlant |
P25392
|
FINISHED |
| Object | PZL Mielec |
—
|
NE NERFINISHED |
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: PZL Mielec | Statement: [Mielec, hasIndustrialPlant, PZL Mielec]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PZL Mielec Context triple: [Mielec, hasIndustrialPlant, PZL Mielec]
-
A.
PZL Mielec
chosen
PZL Mielec is a major Polish aerospace and defense manufacturer known for producing military and civilian aircraft and components.
-
B.
PZL Świdnik
PZL Świdnik is a major Polish aerospace manufacturer best known for producing helicopters and other aircraft, and is a key part of Poland’s defense and aviation industry.
-
C.
PZL-Kalisz
PZL-Kalisz is a Polish aerospace and defense manufacturer best known for producing aircraft engines and related components for both military and civilian applications.
-
D.
PZL-Wrocław
PZL-Wrocław is a Polish aerospace and defense manufacturer known for producing and servicing military aircraft and related equipment.
-
E.
PZL-104 Wilga
The PZL-104 Wilga is a Polish short takeoff and landing (STOL) utility aircraft widely used for roles such as glider towing, parachute training, and general aviation tasks.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee62c9494081909efa74e189454dc6 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 16, 2026, 5:12 p.m.