Triple
T1938395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabethtown, Kentucky |
E41495
|
entity |
| Predicate | hasNearbyInterchange |
P33739
|
FINISHED |
| Object | junction of Interstate 65 and Bluegrass Parkway |
—
|
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 Interstate 65 and Bluegrass Parkway | Statement: [Elizabethtown, Kentucky, hasNearbyInterchange, junction of Interstate 65 and Bluegrass Parkway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyInterchange Context triple: [Elizabethtown, Kentucky, hasNearbyInterchange, junction of Interstate 65 and Bluegrass Parkway]
-
A.
hasBusInterchange
Indicates that one transport-related entity includes, contains, or is associated with a bus interchange facility.
-
B.
interchangeStation
Indicates a station where passengers can transfer between different routes, lines, or modes of transportation.
-
C.
hasAdjacentBusStation
Indicates that one location has a bus station situated directly next to or very near it.
-
D.
isTransportHubBetween
Indicates that a location functions as a central node facilitating transportation connections between two or more other places.
-
E.
adjacentToStation
Indicates that one entity is located next to or immediately beside a station.
- F. None of above. chosen
Provenance (4 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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2c8be648190836580cec77a143f |
completed | March 7, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69abaff07cf88190b4883c5f17f90abd |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb25ef0ec8190b907963e9db0fe04 |
completed | March 7, 2026, 5:06 a.m. |
Created at: March 4, 2026, 7:36 p.m.