Triple
T588815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tutuila |
E17220
|
entity |
| Predicate | countryCode |
P208
|
FINISHED |
| Object | AS |
E10323
|
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: AS | Statement: [Tutuila, countryCode, AS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AS Context triple: [Tutuila, countryCode, AS]
-
A.
AS
chosen
AS is the two-letter ISO 3166-1 alpha-2 country code assigned to American Samoa.
-
B.
AS
AS is the official vehicle registration code assigned to the Indian state of Assam.
-
C.
ASA
ASA is the commonly used abbreviation for the Acoustical Society of America, a leading scientific society dedicated to the study and advancement of acoustics.
-
D.
Ap
Ap is the commonly used abbreviation for the Norwegian Labour Party, a major social-democratic political party in Norway.
-
E.
DA
DA is the official abbreviation for the United States Department of the Army, the federal agency responsible for organizing, training, and equipping the U.S. Army.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9d1e68819096a9b5e7b2e83d6e |
completed | March 1, 2026, 8:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5103be4b881908fcd20c4c781c0a0 |
completed | March 2, 2026, 4:21 a.m. |
Created at: March 1, 2026, 7:33 p.m.