Triple
T11647278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City Airport Train |
E276807
|
entity |
| Predicate | marketingName |
P11546
|
FINISHED |
| Object |
CAT
CAT is a branded express rail service that connects Vienna International Airport with the city center quickly and comfortably.
|
E939195
|
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: CAT | Statement: [City Airport Train, marketingName, CAT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CAT Context triple: [City Airport Train, marketingName, CAT]
-
A.
CAT
The Committee for Advanced Therapies is a scientific body within the European Medicines Agency responsible for assessing advanced therapy medicinal products such as gene, cell, and tissue-engineered therapies.
-
B.
CAT
CAT is a globally recognized industrial brand best known for its heavy construction machinery, engines, and rugged workwear.
-
C.
CAT
CAT is the National Rail station code for Caterham railway station in Surrey, England.
-
D.
CAT
CAT was the civilian airline operated by the CIA in East Asia during the early Cold War, later becoming known as Air America.
-
E.
CAT
CAT is a highly competitive national-level entrance examination in India used for admission to postgraduate management programs such as MBAs at premier institutes.
- 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: CAT Triple: [City Airport Train, marketingName, CAT]
Generated description
CAT is a branded express rail service that connects Vienna International Airport with the city center quickly and comfortably.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CAT Target entity description: CAT is a branded express rail service that connects Vienna International Airport with the city center quickly and comfortably.
-
A.
CAT
CAT is the National Rail station code for Caterham railway station in Surrey, England.
-
B.
CAT
CAT was the civilian airline operated by the CIA in East Asia during the early Cold War, later becoming known as Air America.
-
C.
CAT
CAT is a highly competitive national-level entrance examination in India used for admission to postgraduate management programs such as MBAs at premier institutes.
-
D.
CAT
CAT is a globally recognized industrial brand best known for its heavy construction machinery, engines, and rugged workwear.
-
E.
CAT
The Committee against Torture (CAT) is a United Nations body of independent experts that monitors implementation of the Convention against Torture and other cruel, inhuman or degrading treatment or punishment by its State parties.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a2cd9bb0819093d107204bed2fe0 |
completed | April 10, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef1381a49c81909d849edbfab7448e |
completed | April 27, 2026, 7:42 a.m. |
| NEDg | Description generation | batch_69ef3550fae881909246cd4cca047a19 |
completed | April 27, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ef519f95488190b4b5a167aa930133 |
completed | April 27, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:39 p.m.