Triple
T15516933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lonoke, Arkansas |
E368856
|
entity |
| Predicate | distanceToLittleRockInMiles |
P73646
|
FINISHED |
| Object | approximately 23 |
—
|
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 23 | Statement: [Lonoke, Arkansas, distanceToLittleRockInMiles, approximately 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLittleRockInMiles Context triple: [Lonoke, Arkansas, distanceToLittleRockInMiles, approximately 23]
-
A.
distanceToLittleRock
chosen
Indicates the spatial distance between a given entity and the location of Little Rock.
-
B.
distanceToStLouis
Indicates the measured distance between a given entity’s location and the city of St. Louis.
-
C.
distanceToMemphisApproxMiles
Indicates an approximate distance, measured in miles, between a given entity’s location and the city of Memphis.
-
D.
distanceToLouisianaBorderInMiles
Indicates the numerical distance, measured in miles, from a given location to the border of the state of Louisiana.
-
E.
distanceToMemphisKm
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Memphis.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e04033303c8190a87b6384f68a6921 |
completed | April 16, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69ded2896a9c8190a8b9627deb3c17b4 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 4:02 a.m.