Triple
T16913932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smartwings |
E410272
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Smartwings |
E410272
|
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: Smartwings | Statement: [Smartwings, hasBrand, Smartwings]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smartwings Context triple: [Smartwings, hasBrand, Smartwings]
-
A.
Smartwings
chosen
Smartwings is a Czech low-cost airline based in Prague that operates scheduled and charter flights across Europe and to selected leisure destinations worldwide.
-
B.
Eneco
Eneco is a Dutch energy company focused on sustainable electricity, gas, and heat production and supply in the Netherlands and surrounding regions.
-
C.
E-CO Energi
E-CO Energi is a Norwegian energy company primarily involved in the production and distribution of hydroelectric power.
-
D.
WeMo
WeMo is a brand of smart home devices, such as smart plugs and switches, that allow users to control household electronics remotely via apps and voice assistants.
-
E.
Kenergy
Kenergy is a playful pop-culture term capturing the exuberant, slightly oblivious yet endearing masculine vibe embodied by Ryan Gosling’s portrayal of Ken in the Barbie movie.
- 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3ca3f1a2c8190a512ccc09a080eb4 |
completed | April 18, 2026, 6:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01232b75508190bcceaf0d338f8d02 |
completed | May 11, 2026, 12:30 a.m. |
Created at: April 10, 2026, 5:30 a.m.