Triple
T35795447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Australian Grand Prix |
E1034817
|
entity |
| Predicate | redFlagReason |
P181658
|
FINISHED |
| Object | Fernando Alonso and Esteban Gutiérrez crash |
—
|
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: Fernando Alonso and Esteban Gutiérrez crash | Statement: [2016 Australian Grand Prix, redFlagReason, Fernando Alonso and Esteban Gutiérrez crash]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: redFlagReason Context triple: [2016 Australian Grand Prix, redFlagReason, Fernando Alonso and Esteban Gutiérrez crash]
-
A.
reasonForRedFlag
chosen
Indicates that something serves as the underlying cause or justification for a particular warning, concern, or red flag.
-
B.
redFlags
Indicates that one entity identifies or associates warning signs, concerns, or problematic indicators with another entity or situation.
-
C.
reasonForDefect
Indicates the cause or underlying reason that led to the occurrence of a particular defect.
-
D.
condemnationReason
Indicates the reason or grounds for which something or someone is condemned or judged negatively.
-
E.
reasonForReturn
Indicates the reason or cause why an item, product, or entity is being sent back or returned.
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a25431b481908e39e953b207b6be |
completed | May 3, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:06 p.m.