Triple
T31916345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manassas area, Virginia |
E814840
|
entity |
| Predicate | distanceToWashingtonDCApprox |
P15076
|
FINISHED |
| Object | about 30 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: about 30 miles | Statement: [Manassas area, Virginia, distanceToWashingtonDCApprox, about 30 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToWashingtonDCApprox Context triple: [Manassas area, Virginia, distanceToWashingtonDCApprox, about 30 miles]
-
A.
distanceToWashingtonDC
chosen
Indicates the physical distance between a given location and Washington, D.C.
-
B.
distanceFromPortWashington
Indicates the measured distance between a given location and Port Washington.
-
C.
distanceToWashingtonMonument
Indicates the physical distance between a given entity’s location and the Washington Monument.
-
D.
distanceToSeattle
Indicates the measured or calculated distance between a given entity’s location and the city of Seattle.
-
E.
distanceToPhiladelphia
Indicates the spatial distance between a given entity’s location and the city of Philadelphia.
- 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_69f348f109d88190b5005372c53d2fcd |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a0301c45274819083b0dd9d335f7ee0 |
completed | May 12, 2026, 10:32 a.m. |
| PD | Predicate disambiguation | batch_6a03015c272481908a7bfe81befb1764 |
completed | May 12, 2026, 10:30 a.m. |
Created at: May 1, 2026, 12:02 a.m.