Triple
T28687027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oakley, Kansas |
E729161
|
entity |
| Predicate | nearestMajorInterstateJunction |
P16027
|
FINISHED |
| Object | junction of I-70 and US-83 |
—
|
LITERAL 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: junction of I-70 and US-83 | Statement: [Oakley, Kansas, nearestMajorInterstateJunction, junction of I-70 and US-83]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestMajorInterstateJunction Context triple: [Oakley, Kansas, nearestMajorInterstateJunction, junction of I-70 and US-83]
-
A.
nearestInterstateHighway
Indicates that one interstate highway is the closest in distance to a given location or route compared to all other interstate highways.
-
B.
nearestInterstateExit
Indicates the relationship where a given location is associated with the closest interstate highway exit to it.
-
C.
nearInterstate
Indicates that one entity is located close to or in the immediate vicinity of an interstate highway.
-
D.
motorwayJunctionNearby
chosen
Indicates that a motorway junction is located close to the referenced entity.
-
E.
nearestTurnpikeInterchange
Indicates that one location is the closest turnpike interchange to another specified location.
- F. None of above.
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_69f043e60b6c8190ac2cd042e77fe6e9 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 28, 2026, 5:33 a.m.