Triple
T15760666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Route 160 |
E382087
|
entity |
| Predicate | passesThroughState |
P3448
|
FINISHED |
| Object | Missouri |
E19676
|
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: Missouri | Statement: [U.S. Route 160, passesThroughState, Missouri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Missouri Context triple: [U.S. Route 160, passesThroughState, Missouri]
-
A.
Missouri
chosen
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.
-
B.
Missori
Missori is an underground station on Milan Metro’s Line 3 serving the central area of Milan, Italy.
-
C.
Mont
Mont is a family surname associated with the character Michael Mont.
-
D.
Mont
Mont is a small village in the municipality of Vielha e Mijaran in the Val d'Aran region of Catalonia, Spain.
-
E.
Ozark
Ozark is a dark crime drama television series that follows a financial planner who relocates his family to the Missouri Ozarks to launder money for a Mexican drug cartel.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b52c548190a0ffa4493a4eb15c |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff8774eda08190a6231b4fd5027e6f |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:47 a.m.