Triple
T911877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Missouri |
E19676
|
entity |
| Predicate | postalAbbreviation |
P43
|
FINISHED |
| Object | MO |
E56571
|
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: MO | Statement: [Missouri, postalAbbreviation, MO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MO Context triple: [Missouri, postalAbbreviation, MO]
-
A.
MO
chosen
MO is the two-letter ISO 3166 country code assigned to the Macao Special Administrative Region of China.
-
B.
MA
MA is the two-letter ISO 3166-1 alpha-2 country code assigned to Morocco.
-
C.
Missouri
Missouri is a U.S. state in the Midwest known for its major cities like St. Louis and Kansas City, its role as a historic gateway to the American West, and its diverse mix of agricultural and industrial economies.
-
D.
ONT
ONT is the IATA airport code for Ontario International Airport, a commercial airport serving the Inland Empire region of Southern California.
-
E.
Iowa
Iowa is a Midwestern U.S. state known for its extensive agriculture, especially corn and soybean production, and its role in national politics through the Iowa caucuses.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2de5b008190851852331db41324 |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c73d5bdc8190828cdf9f54e33a46 |
completed | March 4, 2026, 5:46 a.m. |
Created at: March 1, 2026, 7:39 p.m.