Triple
T5021839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bourg-la-Reine |
E112868
|
entity |
| Predicate | commuterRole |
P8652
|
FINISHED |
| Object | bedroom community for Paris |
—
|
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: bedroom community for Paris | Statement: [Bourg-la-Reine, commuterRole, bedroom community for Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commuterRole Context triple: [Bourg-la-Reine, commuterRole, bedroom community for Paris]
-
A.
transportationRole
Indicates a role or function that an entity has specifically in the context of providing, operating, or supporting transportation.
-
B.
urbanRole
chosen
Indicates the function, status, or role that an entity holds within an urban or city context.
-
C.
commuterServiceTo
Indicates a transportation service that regularly carries commuters to a specified destination.
-
D.
transportRole
Indicates that an entity participates in a transportation process with a specific functional role (e.g., carrier, passenger, cargo, or operator).
-
E.
hasCommuterOrientation
Indicates that an entity is designed or intended primarily for use by commuters, emphasizing suitability for regular travel between home and work or study.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73656edc8190b802ad38d9552b58 |
completed | March 20, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69bd714ecfe08190b5830cfc1c74fa17 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:36 p.m.