Triple
T23991099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurdman station |
E605068
|
entity |
| Predicate | hasHeatedAreas |
P34898
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hurdman station, hasHeatedAreas, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHeatedAreas Context triple: [Hurdman station, hasHeatedAreas, yes]
-
A.
hasPlatformHeaters
Indicates that a platform is equipped with heaters to provide warmth or prevent ice and snow accumulation.
-
B.
hasHeating
chosen
Indicates that an entity is equipped with or provides a heating system or heating capability.
-
C.
hasThermalCharacteristic
Indicates that an entity possesses a specific thermal property or behavior, such as conductivity, capacity, or response to temperature.
-
D.
hasThermalActivity
Indicates that an entity exhibits or is associated with heat-related phenomena such as heating, cooling, or temperature change.
-
E.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
- 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_69e295463f7c8190b1c19dbd114641b9 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d38b37648190afb003cded3a7484 |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:37 p.m.