Triple
T13327253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ASEA |
E317471
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | ASEA |
E317471
|
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: ASEA | Statement: [ASEA, shortName, ASEA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ASEA Context triple: [ASEA, shortName, ASEA]
-
A.
ASEA
chosen
ASEA was a major Swedish electrical engineering and power company that became a global leader in industrial technology before merging to form ABB.
-
B.
ASEA
ASEA is the acronym for the African Securities Exchanges Association, a regional body that promotes the development and integration of stock exchanges across Africa.
-
C.
ASEA-UNINET
ASEA-UNINET is an international academic network that promotes cooperation in higher education and research between universities in Europe and Southeast Asia.
-
D.
AGEA
AGEA is a major Argentine media company best known for publishing leading newspapers and magazines, including Elle Argentina.
-
E.
ADESA
ADESA is a major North American vehicle auction and remarketing company that provides wholesale used-vehicle auctions and related services to automotive dealers, manufacturers, and fleet operators.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9992d3b0881909732fbb8db98e44c |
completed | April 11, 2026, 12:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7266f70088190a518e273af507361 |
completed | May 3, 2026, 10:41 a.m. |
Created at: April 9, 2026, 9:30 p.m.