Triple
T14904371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nevertire |
E360088
|
entity |
| Predicate | distanceFromNyngan_km |
P116607
|
FINISHED |
| Object | approximately 64 |
—
|
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 64 | Statement: [Nevertire, distanceFromNyngan_km, approximately 64]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromNyngan_km Context triple: [Nevertire, distanceFromNyngan_km, approximately 64]
-
A.
distanceToWinnemucca
Indicates the spatial distance between a given entity’s location and the location of Winnemucca.
-
B.
distanceFromReno
Indicates the spatial distance between a given entity and the location Reno.
-
C.
distanceFromLasVegas
Indicates the measured distance between a given place or object and the city of Las Vegas.
-
D.
distanceToNepalgunj_km
Indicates the physical distance, measured in kilometers, between a given location and Nepalgunj.
-
E.
distanceFromSaltLakeCity
Indicates the measured distance between a given location and Salt Lake City.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded60cd5588190b1efecc2b220da69 |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a4a14a88190951bb8f4c60bd37b |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:12 a.m.