Triple
T596243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dubai Tram |
E17388
|
entity |
| Predicate | fareSystem |
P395
|
FINISHED |
| Object |
Nol card
The Nol card is a rechargeable smart card used for paying fares across Dubai’s public transportation network, including metro, buses, trams, and water buses.
|
E74359
|
NE FINISHED |
How this triple was built (4 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: Nol card | Statement: [Dubai Tram, fareSystem, Nol card]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nol card Context triple: [Dubai Tram, fareSystem, Nol card]
-
A.
CharlieCard
The CharlieCard is a reusable contactless smart card used to pay fares on Boston's MBTA public transit system.
-
B.
Cardiac Cards
Cardiac Cards is a nickname for the former St. Louis Cardinals NFL team, referencing their dramatic, late-game comebacks and close finishes.
-
C.
Presto card
The Presto card is a reloadable smart card used for paying public transit fares across the Greater Toronto and Hamilton Area and other regions in Ontario, Canada.
-
D.
Calling Cards
Calling Cards is a program section of the Telluride Film Festival that showcases emerging filmmakers’ early or breakthrough works.
-
E.
Clipper card
The Clipper card is a reloadable contactless smart card used to pay fares across multiple public transit systems in the San Francisco Bay Area.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Nol card Triple: [Dubai Tram, fareSystem, Nol card]
Generated description
The Nol card is a rechargeable smart card used for paying fares across Dubai’s public transportation network, including metro, buses, trams, and water buses.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nol card Target entity description: The Nol card is a rechargeable smart card used for paying fares across Dubai’s public transportation network, including metro, buses, trams, and water buses.
-
A.
CharlieCard
The CharlieCard is a reusable contactless smart card used to pay fares on Boston's MBTA public transit system.
-
B.
Cardiac Cards
Cardiac Cards is a nickname for the former St. Louis Cardinals NFL team, referencing their dramatic, late-game comebacks and close finishes.
-
C.
Presto card
The Presto card is a reloadable smart card used for paying public transit fares across the Greater Toronto and Hamilton Area and other regions in Ontario, Canada.
-
D.
Calling Cards
Calling Cards is a program section of the Telluride Film Festival that showcases emerging filmmakers’ early or breakthrough works.
-
E.
Clipper card
The Clipper card is a reloadable contactless smart card used to pay fares across multiple public transit systems in the San Francisco Bay Area.
- F. None of above. chosen
Provenance (5 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bd3e5e08190be95cb2009aad42d |
completed | March 1, 2026, 8:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a518c766508190ae39b6e254a07bc3 |
completed | March 2, 2026, 4:57 a.m. |
| NEDg | Description generation | batch_69a5194215848190874442451c32a10b |
completed | March 2, 2026, 4:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a519d2e46881909d00ff279bd4a13e |
completed | March 2, 2026, 5:02 a.m. |
Created at: March 1, 2026, 7:33 p.m.