Triple
T969802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DE30AC locomotive |
E20919
|
entity |
| Predicate | usedOnServiceType |
P11331
|
FINISHED |
| Object | diesel territory commuter 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: diesel territory commuter trains | Statement: [DE30AC locomotive, usedOnServiceType, diesel territory commuter trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOnServiceType Context triple: [DE30AC locomotive, usedOnServiceType, diesel territory commuter trains]
-
A.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
B.
usedOnMode
chosen
Indicates that something is applied, operated, or functions specifically in a given mode or operational setting.
-
C.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
-
D.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
E.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b4497d688190b59c3a195e377080 |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a579888190afb489ac9fe8391c |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.