Triple
T1298701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monroe, North Carolina |
E27711
|
entity |
| Predicate | distanceToCharlotte |
P28399
|
FINISHED |
| Object | approximately 25 miles southeast |
—
|
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 25 miles southeast | Statement: [Monroe, North Carolina, distanceToCharlotte, approximately 25 miles southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCharlotte Context triple: [Monroe, North Carolina, distanceToCharlotte, approximately 25 miles southeast]
-
A.
distanceToCharlestonMi
Indicates the measured distance, in miles, from a given entity or location to Charleston.
-
B.
distanceToPhiladelphia
Indicates the spatial distance between a given entity’s location and the city of Philadelphia.
-
C.
distanceToWashingtonDC
Indicates the physical distance between a given location and Washington, D.C.
-
D.
distanceToNewYorkCity
Indicates the spatial distance between a given entity’s location and New York City.
-
E.
distanceFromBoston
Indicates the spatial distance between a given entity’s location and the city of Boston.
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c3bb3a9c81909db2ad91defd87b6 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bee64d908190b6a9bb479959d523 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c3b9ebdc819098de4d3288201bc1 |
completed | March 1, 2026, 10:54 p.m. |
Created at: March 1, 2026, 7:51 p.m.