Triple
T22647660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valdosta |
E559006
|
entity |
| Predicate | distanceToFloridaBorder |
P49605
|
FINISHED |
| Object | approximately 15 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 15 miles | Statement: [Valdosta, distanceToFloridaBorder, approximately 15 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToFloridaBorder Context triple: [Valdosta, distanceToFloridaBorder, approximately 15 miles]
-
A.
distanceToFlorida
chosen
Indicates the spatial distance between a given entity’s location and the state of Florida.
-
B.
distanceToMexicoBorder
Indicates the measured or estimated distance between a given location or entity and the border of Mexico.
-
C.
distanceFromMiami
Indicates the spatial distance between a given entity’s location and the city of Miami.
-
D.
distanceToCaliforniaBorder
Indicates the measured or specified distance between a given location and the border of the state of California.
-
E.
distanceToUSBorderByRoad_km
Indicates the distance in kilometers from a given location to the nearest point on the United States border when traveling by road.
- 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17039c2bc8190972a7c169b27005c |
completed | April 29, 2026, 2:43 a.m. |
| PD | Predicate disambiguation | batch_69ee6294c4c08190b7e4829f4b9af24b |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:05 p.m.