Triple
T1632533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GE P42DC |
E35287
|
entity |
| Predicate | usedOnService |
P2367
|
FINISHED |
| Object | Amtrak long-distance 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: Amtrak long-distance trains | Statement: [GE P42DC, usedOnService, Amtrak long-distance trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOnService Context triple: [GE P42DC, usedOnService, Amtrak long-distance trains]
-
A.
usedOn
chosen
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
B.
usedOnMode
Indicates that something is applied, operated, or functions specifically in a given mode or operational setting.
-
C.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
D.
serviceWith
Indicates that one entity provides or is associated with a particular service offered to or used by another entity.
-
E.
usedSupport
Indicates that one entity employed or relied on another entity as a means of support or assistance in performing an action or achieving a result.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a96083e7308190abbf025fe8e43abb |
completed | March 5, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69a907cac610819083cafd4396b6d66c |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.