Triple
T9322965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emporia, Virginia |
E224314
|
entity |
| Predicate | distanceToRichmondInMiles |
P78468
|
FINISHED |
| Object | approximately 75 |
—
|
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 75 | Statement: [Emporia, Virginia, distanceToRichmondInMiles, approximately 75]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToRichmondInMiles Context triple: [Emporia, Virginia, distanceToRichmondInMiles, approximately 75]
-
A.
distanceToRichmond
chosen
Indicates the measured distance between a given location or entity and the place named Richmond.
-
B.
locationRelativeToRichmond
Indicates the spatial or geographic position of one place in relation to the reference location Richmond.
-
C.
distanceToBaltimoreInMiles
Indicates the numerical distance, measured in miles, between a given location and the city of Baltimore.
-
D.
distanceToCharlottesville
Indicates the measured spatial distance between a given entity’s location and the location of Charlottesville.
-
E.
distanceToNorfolkVirginia
Indicates the spatial distance between a given entity or location and Norfolk, Virginia.
- 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_69ca8426d48481909596360f7791c7dd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd36f466b08190884abdc56501a0d8 |
completed | April 1, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69cc7a643924819097f01144734901cf |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:38 p.m.