Triple
T4304889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virgin Valley |
E99929
|
entity |
| Predicate | distanceToWinnemucca |
P55034
|
FINISHED |
| Object | about 100 miles northwest |
—
|
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 northwest | Statement: [Virgin Valley, distanceToWinnemucca, about 100 miles northwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToWinnemucca Context triple: [Virgin Valley, distanceToWinnemucca, about 100 miles northwest]
-
A.
distanceFromReno
Indicates the spatial distance between a given entity and the location Reno.
-
B.
distanceToPreston
Indicates the spatial distance between a given entity and the location named Preston.
-
C.
distanceFromSaltLakeCity
Indicates the measured distance between a given location and Salt Lake City.
-
D.
distanceToFlagstaff
Indicates the measured distance between a given entity’s location and the location of Flagstaff.
-
E.
distanceToLosAngeles
Indicates the measured or calculated distance between a given entity’s location and the city of Los Angeles.
- 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_69b345528ebc8190b5abc7e95094792d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350b8e1cc819094ce3d6f6c8da767 |
completed | March 12, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69b347ff45cc8190b0cc335a94cc3d73 |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e06b3ec81909298b1ddd74d37bd |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:09 p.m.