Triple
T14486441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Batalion Parasol |
E359239
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Kedyw |
E106076
|
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: Kedyw | Statement: [Batalion Parasol, partOf, Kedyw]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kedyw Context triple: [Batalion Parasol, partOf, Kedyw]
-
A.
Kedyw
chosen
Kedyw was a special operations and sabotage unit of the Polish underground Home Army that carried out resistance actions against Nazi German occupation during World War II.
-
B.
Kedzie
Kedzie is a Chicago Transit Authority rapid transit station on the Pink Line serving the city's West Side.
-
C.
Kedzie
Kedzie is a Chicago Transit Authority 'L' station on the Brown Line serving the city's Northwest Side.
-
D.
Kwouk
Kwouk is the surname of Burt Kwouk, a British actor best known for playing Cato in the Pink Panther film series.
-
E.
Kiesen
Kiesen is a municipality in the canton of Bern, Switzerland, served by a station on the Bern–Thun railway line.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924ee0f08190baf68318b41fa64d |
completed | April 14, 2026, 7:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd64a925148190992101984895a20b |
completed | May 8, 2026, 4:20 a.m. |
Created at: April 10, 2026, 1:20 a.m.