Triple
T33649535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Four Little Engines |
E862055
|
entity |
| Predicate | featuresRailway |
P143540
|
FINISHED |
| Object | Skarloey Railway |
E245396
|
NE 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: Skarloey Railway | Statement: [Four Little Engines, featuresRailway, Skarloey Railway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresRailway Context triple: [Four Little Engines, featuresRailway, Skarloey Railway]
-
A.
railwayStationFeature
Indicates that a railway station possesses or is characterized by a particular feature, facility, or attribute.
-
B.
railroadEngineeringFeature
Indicates a feature, element, or characteristic specifically related to the design, construction, or operation of railroad engineering systems.
-
C.
railwayFocus
Indicates that something is a primary subject, theme, or point of attention specifically in the context of railways or railway-related matters.
-
D.
transportInfrastructureFeature
chosen
Indicates a relationship where an entity is a specific element or component of transport infrastructure, such as roads, railways, or related facilities.
-
E.
railroadMet
Indicates that two or more railroads encountered or connected with each other at a specific place or time.
- F. None of above.
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_69f349840ba881908e3bfce536aeb92b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01f4d954e08190aff3756955212d67 |
completed | May 11, 2026, 3:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a376f86a3908190803a47787eb3bd0a |
completed | June 21, 2026, 4:58 a.m. |
| PD | Predicate disambiguation | batch_6a01edadb9248190be592287530740a5 |
completed | May 11, 2026, 2:54 p.m. |
Created at: May 1, 2026, 1:42 a.m.