Triple
T6512291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stirling Moss |
E150163
|
entity |
| Predicate | activeYearsInMotorsport |
P18004
|
FINISHED |
| Object | 1948–1962 |
—
|
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: 1948–1962 | Statement: [Stirling Moss, activeYearsInMotorsport, 1948–1962]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: activeYearsInMotorsport Context triple: [Stirling Moss, activeYearsInMotorsport, 1948–1962]
-
A.
activeYearsInSport
Indicates the span of years during which an entity actively participated in a particular sport.
-
B.
activeYearsInCareer
chosen
Indicates the span of time during which an entity was actively engaged in a particular career or professional field.
-
C.
hasMotorsportInvolvement
Indicates that an entity is involved in motorsport, such as through participation, organization, sponsorship, or other direct association with motor racing activities.
-
D.
activeInYears
Indicates that an entity was active or operational during the specified years or year range.
-
E.
activeYearsPeak
Indicates the span of years during which an entity was at the height of its activity or prominence.
- 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_69c687ef291081909d437f035eef1cda |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69f3c5eb88190a56723acd8096dd8 |
completed | March 27, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69c68ab98c78819081743e614df04e1d |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:44 p.m.