Triple
T1326520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia |
E28340
|
entity |
| Predicate | ISO3166-1Alpha2 |
P189
|
FINISHED |
| Object | GE |
E40849
|
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: GE | Statement: [Georgia, ISO3166-1Alpha2, GE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GE Context triple: [Georgia, ISO3166-1Alpha2, GE]
-
A.
GE
chosen
GE is the ISO 3166-1 alpha-2 country code for Georgia, a nation at the crossroads of Eastern Europe and Western Asia.
-
B.
GE
GE is the Swiss canton code for Geneva, a major city and canton in western Switzerland known for its international organizations and financial center.
-
C.
General Electric
General Electric is a major American multinational conglomerate historically known for its leadership in industrial manufacturing, aviation, power, and healthcare technologies.
-
D.
General Motors
General Motors is a major American multinational automotive manufacturer known for brands such as Chevrolet, GMC, Cadillac, and Buick.
-
E.
Ford
Ford is a common English surname borne by numerous notable individuals, including U.S. President Gerald Ford.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1c0a22881909eff0fc6c91a5f41 |
completed | March 1, 2026, 10:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbf3038148190bd945f67e1a619ca |
completed | March 8, 2026, 12:13 a.m. |
Created at: March 1, 2026, 7:55 p.m.