Triple
T22320948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atocha Renfe |
E551781
|
entity |
| Predicate | fareCardAccepted |
P9955
|
FINISHED |
| Object |
Tarjeta Multi
Tarjeta Multi is a rechargeable, contactless public transport card used across the Madrid region’s metro, light rail, and bus networks.
|
E1531805
|
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: Tarjeta Multi | Statement: [Atocha Renfe, fareCardAccepted, Tarjeta Multi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tarjeta Multi Context triple: [Atocha Renfe, fareCardAccepted, Tarjeta Multi]
-
A.
Leap Card
Leap Card is a reusable, contactless smart card used for paying public transport fares across Dublin and other parts of Ireland.
-
B.
Metcard
Metcard was Melbourne’s former magnetic stripe ticketing system used for public transport before the introduction of the Myki smartcard.
-
C.
Q Card
Q Card is a contactless smart fare card used for paying public transportation fares in the Houston METRO transit system.
-
D.
Karta
Karta was a former administrative district or leadership term that historically governed the area later known as Plered.
-
E.
ConnectCard
ConnectCard is a reusable smart fare card used by Pittsburgh Regional Transit riders to pay for public transportation across the Pittsburgh 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: Tarjeta Multi Triple: [Atocha Renfe, fareCardAccepted, Tarjeta Multi]
Generated description
Tarjeta Multi is a rechargeable, contactless public transport card used across the Madrid region’s metro, light rail, and bus networks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tarjeta Multi Target entity description: Tarjeta Multi is a rechargeable, contactless public transport card used across the Madrid region’s metro, light rail, and bus networks.
-
A.
Leap Card
Leap Card is a reusable, contactless smart card used for paying public transport fares across Dublin and other parts of Ireland.
-
B.
Metcard
Metcard was Melbourne’s former magnetic stripe ticketing system used for public transport before the introduction of the Myki smartcard.
-
C.
Q Card
Q Card is a contactless smart fare card used for paying public transportation fares in the Houston METRO transit system.
-
D.
Karta
Karta was a former administrative district or leadership term that historically governed the area later known as Plered.
-
E.
ConnectCard
ConnectCard is a reusable smart fare card used by Pittsburgh Regional Transit riders to pay for public transportation across the Pittsburgh 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15764d3a48190af79ce4642b7f563 |
completed | April 29, 2026, 12:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ad51a87688190ad638880953172c7 |
completed | May 18, 2026, 9 a.m. |
| NEDg | Description generation | batch_6a0ad991a1e48190ad240a20694223fc |
completed | May 18, 2026, 9:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ada2a61b881908a636b2d1d6e4509 |
completed | May 18, 2026, 9:21 a.m. |
Created at: April 16, 2026, 8:42 p.m.