Triple
T36377482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wimbledon gentlemen’s singles 1885 |
E895942
|
entity |
| Predicate | draw |
P185175
|
FINISHED |
| Object | gentlemen’s singles |
—
|
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: gentlemen’s singles | Statement: [Wimbledon gentlemen’s singles 1885, draw, gentlemen’s singles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: draw Context triple: [Wimbledon gentlemen’s singles 1885, draw, gentlemen’s singles]
-
A.
draws
Indicates that one entity creates a visual representation or image of another entity.
-
B.
drawingTool
Indicates a relationship where an entity functions as a tool or instrument used for drawing.
-
C.
drawType
Indicates the method or style by which something is drawn, rendered, or visually represented.
-
D.
drawingModel
Indicates that one entity serves as a drawing or visual representation model used to depict, design, or illustrate another entity.
-
E.
drawingPower
Indicates that one entity derives or extracts energy, strength, or functional capability from another source.
- F. None of above. chosen
Provenance (4 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_69f76e51d358819092bbc5f119f49476 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb3ff1b08190802b1063d55d3923 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a611a081908dd6aec1df3f4d7f |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7bb3f23f48190b0b9c2d667e09b52 |
completed | May 3, 2026, 9:16 p.m. |
Created at: May 3, 2026, 4:10 p.m.