Triple
T32547690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metrebus Roma |
E831888
|
entity |
| Predicate | supportsContactlessCard |
P15672
|
FINISHED |
| Object |
Metrebus card
The Metrebus card is a rechargeable contactless smart card used for accessing public transportation services in Rome and the surrounding Lazio region.
|
E2011865
|
NE FINISHED |
How this triple was built (3 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: Metrebus card | Statement: [Metrebus Roma, supportsContactlessCard, Metrebus card]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Metrebus card Triple: [Metrebus Roma, supportsContactlessCard, Metrebus card]
Generated description
The Metrebus card is a rechargeable contactless smart card used for accessing public transportation services in Rome and the surrounding Lazio region.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsContactlessCard Context triple: [Metrebus Roma, supportsContactlessCard, Metrebus card]
-
A.
supportsTapToPay
chosen
Indicates that an entity enables or is compatible with tap-to-pay (contactless) payment functionality.
-
B.
supportsCardlessIdentification
Indicates that an entity enables identification or authentication of a person without requiring a physical card.
-
C.
supportsCardRegistration
Indicates that an entity provides the capability to register a payment or identification card for use within a system or service.
-
D.
supportsSmartcards
Indicates that one entity provides compatibility with or the ability to use smartcard-based functionality for another entity.
-
E.
supportsLoyaltyCards
Indicates that an entity provides functionality to accept, manage, or work with loyalty cards for rewards or benefits.
- F. None of above.
Provenance (6 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_69f34925fd08819084cfe4ec566cb704 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a347b86bca88190b44ba45d3aff9879 |
completed | June 18, 2026, 11:13 p.m. |
| NEDg | Description generation | batch_6a347c79f5ac8190a1872e7c696448dc |
completed | June 18, 2026, 11:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a347d4eb5248190927ba63b7a5094f0 |
completed | June 18, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:02 a.m.