Triple
T10568699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matinicus Isle, Maine |
E249420
|
entity |
| Predicate | countryAbbreviation |
P19525
|
FINISHED |
| Object | US |
E391575
|
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: US | Statement: [Matinicus Isle, Maine, countryAbbreviation, US]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: US Context triple: [Matinicus Isle, Maine, countryAbbreviation, US]
-
A.
US
US is the IATA airline designator code assigned to the former American airline US Airways.
-
B.
US
chosen
The US, or United States, is a large federal republic in North America composed of 50 states and known as one of the world's most influential economic and political powers.
-
C.
US
The US, or United States, is a large federal republic in North America composed of 50 states and known as a major global economic and political power.
-
D.
US
The US, or United States, is a federal republic in North America composed of 50 states and known as one of the world’s largest economic and military powers.
-
E.
US
US is the commonly used abbreviation for the University of Szczecin, a public higher education institution in Szczecin, Poland.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5272ff53c8190ae7c399d49b585f5 |
completed | April 7, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95e7396a4819082cc73c736636fb9 |
completed | April 10, 2026, 8:32 p.m. |
Created at: April 6, 2026, 12:37 p.m.