Triple
T18845858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO 3166-2:OM |
E460910
|
entity |
| Predicate | countryCode |
P208
|
FINISHED |
| Object | OM |
—
|
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: OM | Statement: [ISO 3166-2:OM, countryCode, OM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OM Context triple: [ISO 3166-2:OM, countryCode, OM]
-
A.
OM
OM is the post-nominal abbreviation used by members of the Order of Merit, a prestigious British honor recognizing distinguished service in the armed forces, science, art, literature, or the promotion of culture.
-
B.
OM
OM is an American experimental rock band known for its hypnotic, drone-influenced sound and spiritually themed compositions.
-
C.
OM
chosen
OM is the two-letter ISO 3166-1 alpha-2 country code assigned to Oman for international identification and data standards.
-
D.
OM
OM is the commonly used abbreviation for Olympique de Marseille, a major French professional football club based in Marseille.
-
E.
OM
OM was an Italian manufacturer known for producing vehicles such as the Milan series 1500 Peter Witt trams as well as trucks and other industrial transport equipment.
- 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5b8ee96988190bf247b986777945c |
completed | April 20, 2026, 5:26 a.m. |
Created at: April 10, 2026, 11:56 a.m.