Triple
T19574516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bear Island (Great Bear Lake) |
E489816
|
entity |
| Predicate | hasCountryCode |
P189
|
FINISHED |
| Object | CA |
—
|
NE NERFINISHED |
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: CA | Statement: [Bear Island (Great Bear Lake), hasCountryCode, CA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CA Context triple: [Bear Island (Great Bear Lake), hasCountryCode, CA]
-
A.
CA
chosen
CA is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Canada in international standards and systems.
-
B.
CA
CA is the IATA airline designator assigned to Air China, the flag carrier of the People's Republic of China.
-
C.
CA
CA is the vehicle registration code used on license plates for the Italian city of Cagliari.
-
D.
CA
CA is the two-letter U.S. postal abbreviation for the state of California.
-
E.
CA
CA is the commonly used abbreviation for Club Africain, a major Tunisian multi-sport club best known for its football team based in Tunis.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6402333dc8190bdffb1da68e2c76b |
completed | April 20, 2026, 3:02 p.m. |
Created at: April 10, 2026, 1:42 p.m.