Triple
T2111778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crescent |
E42519
|
entity |
| Predicate | usesDieselLocomotive |
P31795
|
FINISHED |
| Object | south of Washington, D.C. |
—
|
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: south of Washington, D.C. | Statement: [Crescent, usesDieselLocomotive, south of Washington, D.C.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDieselLocomotive Context triple: [Crescent, usesDieselLocomotive, south of Washington, D.C.]
-
A.
hasLocomotive
Indicates that one entity possesses or is equipped with a locomotive as part of its composition or operation.
-
B.
locomotiveWorks
Indicates a relationship where an entity is a facility or company that builds, repairs, or maintains locomotives.
-
C.
associatedWithLocomotive
chosen
Indicates a relationship where something is connected or related to a locomotive, such as by use, function, origin, or context.
-
D.
usesRollingStock
Indicates that one entity employs or operates specific rolling stock (such as rail vehicles) in its activities or services.
-
E.
locomotiveNumber
Indicates the identifying number assigned to a locomotive in the relationship.
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb0369a88190af02f0e4e05e2511 |
completed | March 7, 2026, 5:43 a.m. |
| PD | Predicate disambiguation | batch_69abb7ba08948190a3c236bb53ee4257 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.