Triple
T11929228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soko G-2 Galeb |
E283866
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | SOKO |
E944871
|
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: SOKO | Statement: [Soko G-2 Galeb, manufacturer, SOKO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SOKO Context triple: [Soko G-2 Galeb, manufacturer, SOKO]
-
A.
SOKO
chosen
SOKO was a Yugoslav aircraft manufacturer known for producing military and training aircraft, including the Soko J-22 Orao attack jet.
-
B.
SOKOM
SOKOM is the Danish Special Operations Command, the unified headquarters responsible for overseeing Denmark’s elite special operations forces.
-
C.
SOK
SOK is the abbreviation for the Swedish Olympic Committee, the organization responsible for overseeing Sweden's participation in the Olympic Games.
-
D.
Saho
Saho is a Cushitic language spoken primarily by the Saho people in Eritrea and neighboring regions of the Horn of Africa.
-
E.
Sukošan
Sukošan is a coastal village and popular tourist destination on the Adriatic Sea in Croatia, known for its marina and beaches near the city of Zadar.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90303a9a88190a4044e6310ba9b4b |
completed | April 10, 2026, 2:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f440611e648190b2c47b43f02d2e4b |
completed | May 1, 2026, 5:55 a.m. |
Created at: April 8, 2026, 9:45 p.m.