Triple
T1666141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese Grand Prix |
E36015
|
entity |
| Predicate | usesDRS |
P30567
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Chinese Grand Prix, usesDRS, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDRS Context triple: [Chinese Grand Prix, usesDRS, yes]
-
A.
usesDRM
Indicates that one entity applies digital rights management (DRM) controls or technologies to another entity (such as content, software, or media).
-
B.
usedSupport
Indicates that one entity employed or relied on another entity as a means of support or assistance in performing an action or achieving a result.
-
C.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
D.
usesDevice
Indicates that one entity operates, employs, or relies on a particular device to perform an action or achieve a purpose.
-
E.
usesIndicator
Indicates that one entity employs or relies on another entity as an indicator, signal, or metric for assessment, decision-making, or interpretation.
- 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa994f92b0819084ee2f6a672334b9 |
completed | March 6, 2026, 9:07 a.m. |
| PD | Predicate disambiguation | batch_69a907d2475c8190b7ec7dccd3335eb1 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a94192abc0819092fc00fef9d53bcb |
completed | March 5, 2026, 8:40 a.m. |
Created at: March 4, 2026, 7:29 p.m.