Triple
T649251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro Bike Share |
E11308
|
entity |
| Predicate | rentalModel |
P17722
|
FINISHED |
| Object | short-term bike rental |
—
|
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: short-term bike rental | Statement: [Metro Bike Share, rentalModel, short-term bike rental]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rentalModel Context triple: [Metro Bike Share, rentalModel, short-term bike rental]
-
A.
annualRentAmount
Indicates the amount of rent that is charged or paid over the course of one year in the described relationship.
-
B.
rideType
Indicates the specific category or mode of transportation involved in a ride (e.g., standard, shared, premium).
-
C.
reservationSystem
Indicates a system or process that manages the creation, modification, and tracking of reservations or bookings between parties.
-
D.
annualRentCurrency
Indicates the currency in which the annual rent amount is specified.
-
E.
residenceType
Indicates the kind or category of dwelling or living arrangement associated with an entity.
- F. None of above. chosen
Provenance (4 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f31e70c81909a2ac1d939f7ec07 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0eade081909c47e85ed55f808d |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49df0de3c81909721eb391ec94031 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.