Triple
T903784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisbon Tramway |
E19501
|
entity |
| Predicate | hasOperatingEnvironment |
P9320
|
FINISHED |
| Object | mixed traffic with road vehicles |
—
|
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: mixed traffic with road vehicles | Statement: [Lisbon Tramway, hasOperatingEnvironment, mixed traffic with road vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOperatingEnvironment Context triple: [Lisbon Tramway, hasOperatingEnvironment, mixed traffic with road vehicles]
-
A.
hasEnvironmentType
Indicates that an entity is associated with or occurs within a specific type or category of environment.
-
B.
primaryOperatingEnvironment
chosen
Indicates the main environment, platform, or context in which an entity is primarily designed to operate or function.
-
C.
supportsEnvironment
Indicates that one entity provides the necessary conditions, compatibility, or resources for another entity to operate or exist within a particular environment.
-
D.
operatesSystem
Indicates that an entity actively controls, manages, or runs a particular system.
-
E.
operatingSystem
Indicates that one entity is the operating system running on, or used by, another entity.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad58334881908df191140b786780 |
completed | March 1, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69a4aa98caec8190bbcc38320090f058 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.