Triple
T34453550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line T2 (Rouen) |
E884440
|
entity |
| Predicate | urbanRailClassification |
P114460
|
FINISHED |
| Object | light rail |
—
|
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: light rail | Statement: [Line T2 (Rouen), urbanRailClassification, light rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanRailClassification Context triple: [Line T2 (Rouen), urbanRailClassification, light rail]
-
A.
urbanRailCategory
chosen
Indicates the classification of an urban rail system according to its type or category (e.g., metro, tram, light rail).
-
B.
urbanRailway
Indicates a relationship where a railway system operates within or primarily serves an urban or metropolitan area.
-
C.
urbanRailHubFor
Indicates that a location functions as a central node or interchange point within an urban rail network for a given area or set of lines.
-
D.
cityRailStyle
Indicates that something follows or embodies the characteristic style, design, or operational pattern associated with a city rail system.
-
E.
railSystemType
Indicates the specific category or classification of a rail transportation system that an entity belongs to or operates within.
- 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_69f349c607688190b553539d14901a35 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f72ad38a208190b4bdc828297f86ad |
completed | May 3, 2026, 11 a.m. |
| PD | Predicate disambiguation | batch_69f72a0243988190a43b8ea22457cd30 |
completed | May 3, 2026, 10:57 a.m. |
Created at: May 1, 2026, 2 a.m.