Triple
T829856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martinsburg station |
E17938
|
entity |
| Predicate | isTerminalFor |
P2066
|
FINISHED |
| Object | some MARC Brunswick Line trains |
—
|
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: some MARC Brunswick Line trains | Statement: [Martinsburg station, isTerminalFor, some MARC Brunswick Line trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTerminalFor Context triple: [Martinsburg station, isTerminalFor, some MARC Brunswick Line trains]
-
A.
isMajorTerminalOf
Indicates that one entity serves as a primary or main terminal (such as a key endpoint or hub) for another entity within a system or network.
-
B.
hasSubTerminal
Indicates that an entity includes or is associated with a subordinate or lower-level terminal element within a hierarchical structure.
-
C.
isDestinationFor
chosen
Indicates that one entity serves as the endpoint or target location that another entity is intended to reach or be directed toward.
-
D.
terminusType
Indicates the specific kind or role of an endpoint or terminal within a route, network, or process.
-
E.
hasVIPTerminal
Indicates that one entity possesses or provides access to a VIP (very important person) terminal associated with another entity.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abb384988190949d2df65662f76d |
completed | March 1, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69a4aa79a6488190a634388e071ed9b7 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.