Triple
T5837611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gassco |
E129509
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | Gassco AS |
E129509
|
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: Gassco AS | Statement: [Gassco, hasAbbreviation, Gassco AS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gassco AS Context triple: [Gassco, hasAbbreviation, Gassco AS]
-
A.
Gassco
chosen
Gassco is a Norwegian state-owned company responsible for operating the country’s natural gas transportation system and export pipelines.
-
B.
Ørsted
Ørsted is a Danish renewable energy company and one of the world’s leading developers and operators of offshore wind farms.
-
C.
DNO
DNO is the abbreviation for the Defence Nuclear Organisation, a body responsible for overseeing and managing a nation's defence-related nuclear capabilities and programs.
-
D.
MOL Global
MOL Global was a Malaysian online payment solutions provider best known for acquiring the once-popular social networking site Friendster.
-
E.
Gazprom
Gazprom is a Russian state-controlled energy giant and one of the world’s largest producers and exporters of natural gas.
- 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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c034a48750819099ae917ae2b54e6d |
completed | March 22, 2026, 6:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a19a6554819086cdae499f4d2247 |
completed | March 23, 2026, 2:12 a.m. |
Created at: March 22, 2026, 3:54 p.m.