Triple
T23154904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HyperCard |
E578412
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object |
MetaCard
MetaCard is a cross-platform, HyperCard-inspired software environment for building graphical, card-based applications using a high-level scripting language.
|
E1574264
|
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: MetaCard | Statement: [HyperCard, influenced, MetaCard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MetaCard Context triple: [HyperCard, influenced, MetaCard]
-
A.
MCard
MCard is a smart, multi-operator public transport ticketing card used across West Yorkshire for buses and trains.
-
B.
ConnectCard
ConnectCard is a reusable smart fare card used by Pittsburgh Regional Transit riders to pay for public transportation across the Pittsburgh area.
-
C.
Metcard
Metcard was Melbourne’s former magnetic stripe ticketing system used for public transport before the introduction of the Myki smartcard.
-
D.
CardBus
CardBus is a 32-bit PC Card (PCMCIA) expansion standard used in laptops to provide high-speed connectivity for devices such as network cards, modems, and storage adapters.
-
E.
Q Card
Q Card is a contactless smart fare card used for paying public transportation fares in the Houston METRO transit system.
- 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: MetaCard Triple: [HyperCard, influenced, MetaCard]
Generated description
MetaCard is a cross-platform, HyperCard-inspired software environment for building graphical, card-based applications using a high-level scripting language.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MetaCard Target entity description: MetaCard is a cross-platform, HyperCard-inspired software environment for building graphical, card-based applications using a high-level scripting language.
-
A.
MCard
MCard is a smart, multi-operator public transport ticketing card used across West Yorkshire for buses and trains.
-
B.
ConnectCard
ConnectCard is a reusable smart fare card used by Pittsburgh Regional Transit riders to pay for public transportation across the Pittsburgh area.
-
C.
Metcard
Metcard was Melbourne’s former magnetic stripe ticketing system used for public transport before the introduction of the Myki smartcard.
-
D.
CardBus
CardBus is a 32-bit PC Card (PCMCIA) expansion standard used in laptops to provide high-speed connectivity for devices such as network cards, modems, and storage adapters.
-
E.
Q Card
Q Card is a contactless smart fare card used for paying public transportation fares in the Houston METRO transit system.
- 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_69e245fb8de081908f0eba7b5fd75bc4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18efca1f081908ff1c34ba25f40c3 |
completed | April 29, 2026, 4:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c309c3da48190b07c64b10fda58ff |
completed | May 19, 2026, 9:42 a.m. |
| NEDg | Description generation | batch_6a0c31dd458c8190b8e98870dd5e19c5 |
completed | May 19, 2026, 9:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c325f5c248190b35e2c88b384ac31 |
completed | May 19, 2026, 9:50 a.m. |
Created at: April 17, 2026, 4:01 p.m.