Triple
T19457595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SH 165 |
E486772
|
entity |
| Predicate | hasRouteDesignation |
P5539
|
FINISHED |
| Object | SH 165 |
—
|
NE NERFINISHED |
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: SH 165 | Statement: [SH 165, hasRouteDesignation, SH 165]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SH 165 Context triple: [SH 165, hasRouteDesignation, SH 165]
-
A.
SH 165
chosen
SH 165 is a scenic state highway in Colorado that winds through the Wet Mountains and provides access to attractions such as Bishop Castle.
-
B.
SH 155
SH 155 is a Texas state highway that runs through East Texas, connecting several communities and serving as a regional transportation route.
-
C.
SH 152
SH 152 is a Texas state highway that runs across the Texas Panhandle, connecting the cities of Dumas and Pampa and serving as an important east–west route in the region.
-
D.
SH-16
SH-16 is a state highway in Oklahoma that serves as a regional route connecting several towns and rural areas in the state.
-
E.
SH 130
SH 130 is a Texas toll highway known for its high speed limits and role as an alternative route to ease congestion on Interstate 35.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c569a081908b5a71226345a929 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:38 p.m.