Triple
T8463039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haas F1 Team |
E200089
|
entity |
| Predicate | firstPointsFinish |
P21887
|
FINISHED |
| Object | 2016 Australian Grand Prix |
—
|
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: 2016 Australian Grand Prix | Statement: [Haas F1 Team, firstPointsFinish, 2016 Australian Grand Prix]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstPointsFinish Context triple: [Haas F1 Team, firstPointsFinish, 2016 Australian Grand Prix]
-
A.
firstRunningWinner
Indicates that the subject is the first entity to win among those participating in a running event or race.
-
B.
firstWinner
Indicates that the subject is the entity who achieved first place or victory in the referenced event or competition.
-
C.
firstToAchieve
chosen
Indicates that one entity was the earliest or initial entity to accomplish or attain a specified goal, status, or outcome before any others.
-
D.
pointsLeader
Indicates that the subject entity is the current leader in points relative to other entities in a given context or competition.
-
E.
frontRunnerAtStart
Indicates that an entity is the leading competitor or in first position at the beginning of an event or process.
- 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_69ca83198c4c8190a337bf717d1813f5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4a251f08190840a7fc31ff528b5 |
completed | March 31, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:10 p.m.