Triple
T1478883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohio |
E30904
|
entity |
| Predicate | ISOCode |
P208
|
FINISHED |
| Object | US-OH |
E30904
|
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-OH | Statement: [Ohio, ISOCode, US-OH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: US-OH Context triple: [Ohio, ISOCode, US-OH]
-
A.
Ohio
chosen
Ohio is a Midwestern U.S. state known for its diverse economy, major cities like Columbus, Cleveland, and Cincinnati, and its significant role in national politics as a historic swing state.
-
B.
US-ME
US-ME is the ISO 3166-2 code representing the U.S. state of Maine.
-
C.
US
US is the IATA airline designator code assigned to the former American airline US Airways.
-
D.
US-MS
US-MS is the ISO 3166-2 code representing the U.S. state of Mississippi.
-
E.
Texas–New York
Texas–New York refers to the interstate context linking Texas and New York, notably framing sports rivalries such as those between Dallas and New York teams.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c6739d2481909ea8d8e075f62cf3 |
completed | March 1, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad15aff1288190a3e36324d975d482 |
completed | March 8, 2026, 6:22 a.m. |
Created at: March 1, 2026, 8:11 p.m.