Triple
T1277230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mall, London |
E27242
|
entity |
| Predicate | designedToAppearLike |
P18245
|
FINISHED |
| Object | red carpet |
—
|
LITERAL FINISHED |
How this triple was built (2 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: red carpet | Statement: [The Mall, London, designedToAppearLike, red carpet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedToAppearLike Context triple: [The Mall, London, designedToAppearLike, red carpet]
-
A.
isDesignedFor
Indicates that one entity has been created, planned, or optimized specifically to serve the needs, purposes, or use of another entity.
-
B.
isDesignedAs
chosen
Indicates that something has been intentionally created or configured to serve as or function in the role of something else.
-
C.
designedWith
Indicates that one entity was created, planned, or developed using another entity as a tool, method, or guiding basis in its design process.
-
D.
disguisedAs
Indicates that one entity is intentionally presenting itself as, or made to appear as, another entity in order to conceal its true identity.
-
E.
appearsAs
Indicates that one entity is presented, perceived, or manifested in the form, role, or guise of another entity.
- F. None of above.
Provenance (3 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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c31602b8819087a57e8d390cae7a |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4bee0be808190a8ccac6a41851fdd |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.