Triple
T27428131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairlee, Maryland |
E690547
|
entity |
| Predicate | locatedInCountySeatNearby |
P17796
|
FINISHED |
| Object | Chestertown, Maryland |
—
|
NE NERFINISHED |
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: Chestertown, Maryland | Statement: [Fairlee, Maryland, locatedInCountySeatNearby, Chestertown, Maryland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInCountySeatNearby Context triple: [Fairlee, Maryland, locatedInCountySeatNearby, Chestertown, Maryland]
-
A.
locatedInCountySeatOfCounty
Indicates that one entity is located in the county seat city or town of the specified county.
-
B.
locatedInDirectionFromCountySeat
Indicates that one place is situated in a specified compass direction relative to the county seat.
-
C.
hasNearbyCounty
Indicates that one county is geographically close to or directly adjacent to another county.
-
D.
hasMunicipalitySeatNearby
Indicates that the municipality’s administrative seat is located in close proximity to the referenced place or entity.
-
E.
isInCountySeatProximity
chosen
Indicates that one location lies within a defined close distance to the county seat of a given 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_69ef52003fb48190b0f1295246182a86 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69fedfd913f48190bdcd450980868d9a |
completed | May 9, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69fedf58c6e88190821a7156054c9086 |
completed | May 9, 2026, 7:16 a.m. |
Created at: April 27, 2026, 12:41 p.m.