Triple
T6959164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra Railway of California |
E161322
|
entity |
| Predicate | Sierra Railway No. 3 |
P73770
|
FINISHED |
| Object | famous movie locomotive |
—
|
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: famous movie locomotive | Statement: [Sierra Railway of California, Sierra Railway No. 3, famous movie locomotive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Sierra Railway No. 3 Context triple: [Sierra Railway of California, Sierra Railway No. 3, famous movie locomotive]
-
A.
formerRailroad
Indicates that an entity was previously a railroad but no longer functions as one.
-
B.
locomotiveWorks
Indicates a relationship where an entity is a facility or company that builds, repairs, or maintains locomotives.
-
C.
servedByRailroad
Indicates that a location or facility is provided with transportation or service by a railroad line or company.
-
D.
locomotiveNumber
Indicates the identifying number assigned to a locomotive in the relationship.
-
E.
originalRailroadName
Indicates the name of the railroad as it was originally known or designated, before any later changes such as mergers, rebrandings, or renamings.
- F. None of above. chosen
Provenance (4 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6daedbb4c8190b46846fb1265b937 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c0b0a08190b262dfc94992994d |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d9bb57e88190a3a7cec34e3b617f |
completed | March 27, 2026, 7:25 p.m. |
Created at: March 27, 2026, 2:29 p.m.