Triple
T223139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amsterdam Amstel |
E4259
|
entity |
| Predicate | fareSystem |
P395
|
FINISHED |
| Object |
OV-chipkaart
OV-chipkaart is the nationwide contactless smart card system used for paying public transport fares across the Netherlands.
|
E28408
|
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: OV-chipkaart | Statement: [Amsterdam Amstel, fareSystem, OV-chipkaart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OV-chipkaart Context triple: [Amsterdam Amstel, fareSystem, OV-chipkaart]
-
A.
TAP card
The TAP card is a reusable contactless smart card used to pay fares across public transit systems in the Los Angeles County region.
-
B.
CharlieCard
The CharlieCard is a reusable contactless smart card used to pay fares on Boston's MBTA public transit system.
-
C.
NFC
The NFC (National Football Conference) is one of the two conferences in the National Football League, comprising 16 teams that compete for a spot in the Super Bowl.
-
D.
SmarTrip
SmarTrip is a rechargeable contactless smart card used to pay fares on the Washington, D.C. region’s public transit systems.
-
E.
SEPTA Key
SEPTA Key is a contactless smart fare card and payment system used across Philadelphia’s SEPTA public transit network.
- 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: OV-chipkaart Triple: [Amsterdam Amstel, fareSystem, OV-chipkaart]
Generated description
OV-chipkaart is the nationwide contactless smart card system used for paying public transport fares across the Netherlands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: OV-chipkaart Target entity description: OV-chipkaart is the nationwide contactless smart card system used for paying public transport fares across the Netherlands.
-
A.
TAP card
The TAP card is a reusable contactless smart card used to pay fares across public transit systems in the Los Angeles County region.
-
B.
CharlieCard
The CharlieCard is a reusable contactless smart card used to pay fares on Boston's MBTA public transit system.
-
C.
NFC
The NFC (National Football Conference) is one of the two conferences in the National Football League, comprising 16 teams that compete for a spot in the Super Bowl.
-
D.
SmarTrip
SmarTrip is a rechargeable contactless smart card used to pay fares on the Washington, D.C. region’s public transit systems.
-
E.
SEPTA Key
SEPTA Key is a contactless smart fare card and payment system used across Philadelphia’s SEPTA public transit network.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c7194fc8190a2d02d446ae3a75e |
completed | Feb. 28, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a34d96acd88190ae3c8c86bee2572c |
completed | Feb. 28, 2026, 8:18 p.m. |
| NEDg | Description generation | batch_69a351694cf48190a87a4135868cab86 |
completed | Feb. 28, 2026, 8:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a351c25af08190858e4d6644ddd75d |
completed | Feb. 28, 2026, 8:36 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.