Triple
T4779353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landsorganisasjonen i Norge |
E106134
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | LO |
E106135
|
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: LO | Statement: [Landsorganisasjonen i Norge, shortName, LO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LO Context triple: [Landsorganisasjonen i Norge, shortName, LO]
-
A.
LO
chosen
LO is Norway’s largest and most influential trade union confederation, representing a broad spectrum of workers across multiple sectors.
-
B.
LO
LO was the New York Stock Exchange ticker symbol for Lorillard Tobacco Company, a major American tobacco manufacturer best known for brands like Newport.
-
C.
LO
LO is the regional vehicle registration code assigned to the city of Vanadzor in Armenia.
-
D.
LOS
LOS is the IATA airport code for Murtala Muhammed International Airport, the main international gateway serving Lagos, Nigeria.
-
E.
L
L is the vehicle registration code used on license plates for the German city and district of Leipzig.
- 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_69bd43f3074c8190937e7b0a457fe9f1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd658a86288190bc80651840ce6b18 |
completed | March 20, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be43cecc748190a410c262aa2e4b98 |
completed | March 21, 2026, 7:07 a.m. |
Created at: March 20, 2026, 1:21 p.m.