Triple
T20665053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brownsville, Tennessee |
E507861
|
entity |
| Predicate | distanceToMemphisInMiles |
P70714
|
FINISHED |
| Object | about 60 |
—
|
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 60 | Statement: [Brownsville, Tennessee, distanceToMemphisInMiles, about 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMemphisInMiles Context triple: [Brownsville, Tennessee, distanceToMemphisInMiles, about 60]
-
A.
distanceToMemphisApproxMiles
chosen
Indicates an approximate distance, measured in miles, between a given entity’s location and the city of Memphis.
-
B.
distanceToMemphisKm
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Memphis.
-
C.
distanceToNashvilleInMilesApprox
Indicates the approximate distance, measured in miles, between a given entity’s location and Nashville.
-
D.
distanceToKnoxville
Indicates the spatial distance between a given entity’s location and the city of Knoxville.
-
E.
distanceToStLouis
Indicates the measured distance between a given entity’s location and the city of St. Louis.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5c2c6d48190bbfe505cf7d973f9 |
completed | April 20, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:44 a.m.