Triple
T5432804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TVMLKit |
E121535
|
entity |
| Predicate | supportsMarkupLanguage |
P2177
|
FINISHED |
| Object |
TVML
TVML is Apple’s XML-based markup language used to define the user interface and layout for tvOS apps.
|
E121535
|
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: TVML | Statement: [TVMLKit, supportsMarkupLanguage, TVML]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TVML Context triple: [TVMLKit, supportsMarkupLanguage, TVML]
-
A.
TVMLKit
TVMLKit is an Apple framework that lets developers build tvOS apps using TVML templates, JavaScript, and web-like technologies instead of fully native UI code.
-
B.
WML
WML is the National Rail station code for Wilmslow railway station in Cheshire, England.
-
C.
WAP
"WAP" is a 2020 hip hop single by Cardi B featuring Megan Thee Stallion, widely known for its explicit lyrics, viral popularity, and cultural impact.
-
D.
HTM
HTM is the public transport company that operates trams and buses in and around The Hague in the Netherlands.
-
E.
HAL (Hypertext Application Language)
HAL (Hypertext Application Language) is a simple, JSON-based hypermedia format that standardizes how to represent and navigate links and embedded resources in RESTful APIs.
- 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: TVML Triple: [TVMLKit, supportsMarkupLanguage, TVML]
Generated description
TVML is Apple’s XML-based markup language used to define the user interface and layout for tvOS apps.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TVML Target entity description: TVML is Apple’s XML-based markup language used to define the user interface and layout for tvOS apps.
-
A.
TVMLKit
chosen
TVMLKit is an Apple framework that lets developers build tvOS apps using TVML templates, JavaScript, and web-like technologies instead of fully native UI code.
-
B.
WML
WML is the National Rail station code for Wilmslow railway station in Cheshire, England.
-
C.
WAP
"WAP" is a 2020 hip hop single by Cardi B featuring Megan Thee Stallion, widely known for its explicit lyrics, viral popularity, and cultural impact.
-
D.
HTM
HTM is the public transport company that operates trams and buses in and around The Hague in the Netherlands.
-
E.
HAL (Hypertext Application Language)
HAL (Hypertext Application Language) is a simple, JSON-based hypermedia format that standardizes how to represent and navigate links and embedded resources in RESTful APIs.
- F. None of above.
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_69bd463c65f0819082ee6483ab4b466a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8840ade481909dae2eecc77d73b8 |
completed | March 20, 2026, 5:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf41284998819096667ae70180e067 |
completed | March 22, 2026, 1:08 a.m. |
| NEDg | Description generation | batch_69bf4207393c819089b4fc6691a2d076 |
completed | March 22, 2026, 1:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf427e2bd08190b7664922d26e16d2 |
completed | March 22, 2026, 1:14 a.m. |
Created at: March 20, 2026, 2:06 p.m.