Triple
T23640891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Comet |
E583885
|
entity |
| Predicate | modelRailroading |
P152999
|
FINISHED |
| Object | popular subject for model 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: popular subject for model trains | Statement: [Blue Comet, modelRailroading, popular subject for model trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelRailroading Context triple: [Blue Comet, modelRailroading, popular subject for model trains]
-
A.
locomotiveWorks
Indicates a relationship where an entity is a facility or company that builds, repairs, or maintains locomotives.
-
B.
formerRailroad
Indicates that an entity was previously a railroad but no longer functions as one.
-
C.
railroadMet
Indicates that two or more railroads encountered or connected with each other at a specific place or time.
-
D.
formerRailwayZone
Indicates that an entity was previously part of a specified railway administrative zone or system, but is no longer within that zone.
-
E.
railroad
Indicates that one entity constructs, operates, or provides railroad or train transportation services for another entity or area.
- 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_69e248fe1c2c8190ac914d2442ff3d26 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b2808d888190a2198f5efd25f2df |
completed | April 29, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f1233300bc8190ac1639bdca1d7d99 |
completed | April 28, 2026, 9:14 p.m. |
Created at: April 17, 2026, 6:48 p.m.