Triple
T17691836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lympstone Commando railway station |
E441044
|
entity |
| Predicate | adjacentFacilityType |
P75188
|
FINISHED |
| Object | military base |
—
|
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: military base | Statement: [Lympstone Commando railway station, adjacentFacilityType, military base]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentFacilityType Context triple: [Lympstone Commando railway station, adjacentFacilityType, military base]
-
A.
adjacentFacilitySecurityClass
Indicates that two facilities located next to each other share a specified level or classification of security.
-
B.
nearbyFacilityType
chosen
Indicates that a facility of a specified type is located close to a given reference entity or location.
-
C.
adjacentBuildingFunction
Indicates that two buildings located next to each other have a specified functional relationship or usage connection.
-
D.
adjacentToInfrastructure
Indicates that one entity is located directly next to or in immediate proximity to a piece of infrastructure.
-
E.
adjacentToStation
Indicates that one entity is located next to or immediately beside a station.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47152306c819086d483d87348db5d |
completed | April 19, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69e3cde3673c8190a889e14ba1f07dc1 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 10:03 a.m.