Triple
T13019877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TImage |
E322644
|
entity |
| Predicate | supportsGraphicClass |
P32439
|
FINISHED |
| Object |
TMetafile
TMetafile is a Delphi graphics class that represents and handles Windows metafile images, allowing scalable, vector-based drawing to be stored and rendered.
|
E1014704
|
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: TMetafile | Statement: [TImage, supportsGraphicClass, TMetafile]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TMetafile Context triple: [TImage, supportsGraphicClass, TMetafile]
-
A.
TImage
TImage is a VCL component in Delphi used to display and manipulate images within graphical user interfaces.
-
B.
TFile
TFile is a ROOT framework class that provides an interface for creating, reading, and writing ROOT data files used in high-energy physics and data analysis.
-
C.
TIF
TIF is the former New York Stock Exchange ticker symbol for Tiffany & Co., the luxury jewelry and specialty retailer.
-
D.
TIF
TIF is the IATA airport code for Taif Regional Airport, which serves the city of Taif in Saudi Arabia.
-
E.
TIF
TIF is a major annual international trade fair held in Thessaloniki, Greece, showcasing products, services, and innovations from domestic and global exhibitors.
- 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: TMetafile Triple: [TImage, supportsGraphicClass, TMetafile]
Generated description
TMetafile is a Delphi graphics class that represents and handles Windows metafile images, allowing scalable, vector-based drawing to be stored and rendered.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TMetafile Target entity description: TMetafile is a Delphi graphics class that represents and handles Windows metafile images, allowing scalable, vector-based drawing to be stored and rendered.
-
A.
TImage
TImage is a VCL component in Delphi used to display and manipulate images within graphical user interfaces.
-
B.
TFile
TFile is a ROOT framework class that provides an interface for creating, reading, and writing ROOT data files used in high-energy physics and data analysis.
-
C.
TIF
TIF is the IATA airport code for Taif Regional Airport, which serves the city of Taif in Saudi Arabia.
-
D.
TIF
TIF is the former New York Stock Exchange ticker symbol for Tiffany & Co., the luxury jewelry and specialty retailer.
-
E.
TIF
TIF is a major annual international trade fair held in Thessaloniki, Greece, showcasing products, services, and innovations from domestic and global exhibitors.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9804b743c8190810dc5c14bc6d912 |
completed | April 10, 2026, 10:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c116423881908d0de1e04904fbc3 |
completed | May 3, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_69f6c20aff008190a1a10ac02ed08726 |
completed | May 3, 2026, 3:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6c2de143c81908164f5df2b92e5c3 |
completed | May 3, 2026, 3:37 a.m. |
Created at: April 9, 2026, 8:51 p.m.