Triple
T37645915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alcova, Wyoming |
E937036
|
entity |
| Predicate | distanceToCasper |
P206016
|
FINISHED |
| Object | approximately 30 miles |
—
|
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: approximately 30 miles | Statement: [Alcova, Wyoming, distanceToCasper, approximately 30 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCasper Context triple: [Alcova, Wyoming, distanceToCasper, approximately 30 miles]
-
A.
distanceFromJasper
Indicates the spatial distance measured from the reference point or entity named Jasper to another entity or location.
-
B.
distanceFromLasVegas
Indicates the measured distance between a given place or object and the city of Las Vegas.
-
C.
distanceToPalmSprings
Indicates the spatial distance between a given location or entity and Palm Springs.
-
D.
distanceFromTaos
Indicates the spatial distance separating something from the location of Taos.
-
E.
distanceToColumbus
Indicates the spatial distance between a given entity and the location of Columbus.
- 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_69f76ed4fe908190b8061c5c135e0971 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:18 p.m.