Triple
T9560418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forney locomotive |
E230656
|
entity |
| Predicate | hasTypicalService |
P849
|
FINISHED |
| Object | short-haul passenger 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: short-haul passenger trains | Statement: [Forney locomotive, hasTypicalService, short-haul passenger trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalService Context triple: [Forney locomotive, hasTypicalService, short-haul passenger trains]
-
A.
hasServiceTo
Indicates that one entity provides, offers, or operates a service for or directed toward another entity.
-
B.
hasServiceStandard
Indicates that an entity is associated with, or governed by, a defined service standard specifying expected service levels or quality.
-
C.
hasServiceType
chosen
Indicates that an entity is associated with or categorized by a particular type of service.
-
D.
hasSupportService
Indicates that one entity provides or is associated with a support-related service for another entity.
-
E.
typicalServiceStatus
Indicates the usual or standard operational state or condition that a service is expected to be in under normal circumstances.
- 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_69ca847e53a88190a60eed7e02257f10 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd994bde0c8190afcba5cb8fa8b984 |
completed | April 1, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69ccd594d0ac8190a81bc11a3a538167 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:03 p.m.