Triple
T9227772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lusby, Maryland |
E221730
|
entity |
| Predicate | locatedInCountySeatDistance |
P17796
|
FINISHED |
| Object | near Prince Frederick, Maryland |
—
|
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: near Prince Frederick, Maryland | Statement: [Lusby, Maryland, locatedInCountySeatDistance, near Prince Frederick, Maryland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInCountySeatDistance Context triple: [Lusby, Maryland, locatedInCountySeatDistance, near Prince Frederick, Maryland]
-
A.
isInCountySeatProximity
chosen
Indicates that one location lies within a defined close distance to the county seat of a given county.
-
B.
hasCountyCapitalDistance
Indicates a distance relationship specifying how far a county is from its capital.
-
C.
districtHeadquartersDistance
Indicates the distance between a place and its corresponding district headquarters.
-
D.
isInCountySeatOf
Indicates that one entity is located within the town or city that serves as the administrative center (county seat) of a specified county.
-
E.
containsCountySeat
Indicates that one administrative region or area includes within its boundaries the designated county seat location of a county.
- 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_69ca83ec8db08190a9110df8232885d2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccdaa0a7608190b10d913e5e3d1b3e |
completed | April 1, 2026, 8:43 a.m. |
| PD | Predicate disambiguation | batch_69cc7a3daeb481908b0abde3fbc1f1f0 |
completed | April 1, 2026, 1:51 a.m. |
Created at: March 30, 2026, 7:28 p.m.