Triple
T14494325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Centreville, Maryland |
E359450
|
entity |
| Predicate | distanceToAnnapolisInMilesApprox |
P114452
|
FINISHED |
| Object | 25 |
—
|
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: 25 | Statement: [Centreville, Maryland, distanceToAnnapolisInMilesApprox, 25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAnnapolisInMilesApprox Context triple: [Centreville, Maryland, distanceToAnnapolisInMilesApprox, 25]
-
A.
distanceToAnnapolisMiles
Indicates the physical distance, measured in miles, between a given location and Annapolis.
-
B.
distanceToBaltimoreInMiles
Indicates the numerical distance, measured in miles, between a given location and the city of Baltimore.
-
C.
distanceToMontpelierApprox
Indicates an approximate measure of how far one entity is from Montpelier, typically expressed as a distance value.
-
D.
distanceToOceanCity
Indicates the measured distance between a given location and Ocean City.
-
E.
distanceToWashingtonDC
Indicates the physical distance between a given location and Washington, D.C.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de930f34d08190b4b30e54e2f702ed |
completed | April 14, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69de5c4ccba08190a988bfda0bc9f5cb |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:21 a.m.