Triple
T20587407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empire, Nevada |
E505820
|
entity |
| Predicate | distanceToRenoApprox |
P22802
|
FINISHED |
| Object | about 100 miles north |
—
|
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: about 100 miles north | Statement: [Empire, Nevada, distanceToRenoApprox, about 100 miles north]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToRenoApprox Context triple: [Empire, Nevada, distanceToRenoApprox, about 100 miles north]
-
A.
distanceFromReno
chosen
Indicates the spatial distance between a given entity and the location Reno.
-
B.
distanceFromLasVegas
Indicates the measured distance between a given place or object and the city of Las Vegas.
-
C.
distanceToWinnemucca
Indicates the spatial distance between a given entity’s location and the location of Winnemucca.
-
D.
distanceToPahrumpNevada
Indicates the spatial distance between a given entity or location and Pahrump, Nevada.
-
E.
distanceToSanBernardino
Indicates the measured distance between a given entity’s location and the location of San Bernardino.
- 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_69e0b4b9669c8190b8e81fc72817d42c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a977fb18819085fee5cf5d45c1b0 |
completed | April 20, 2026, 10:32 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:40 a.m.