Triple
T28836387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viewliner dining cars |
E728194
|
entity |
| Predicate | trainHVAC |
P72603
|
FINISHED |
| Object | head-end power |
—
|
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: head-end power | Statement: [Viewliner dining cars, trainHVAC, head-end power]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainHVAC Context triple: [Viewliner dining cars, trainHVAC, head-end power]
-
A.
trainHeating
Indicates that a train is equipped with or using a system to provide heating for its interior or its cars.
-
B.
climateControlFeature
chosen
Indicates that an entity includes or supports a function or system for regulating environmental conditions such as temperature, humidity, or airflow.
-
C.
hasHeating
Indicates that an entity is equipped with or provides a heating system or heating capability.
-
D.
thermalControl
Indicates a relationship where one entity regulates, adjusts, or maintains the temperature or thermal conditions of another entity or environment.
-
E.
buildingSystem
Indicates that one entity functions as a system, subsystem, or organized set of components that serves or supports the operation of a building.
- 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_69f0319dc6088190bbfaa206d40ed74a |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 28, 2026, 6:39 a.m.