Triple
T35880653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1936 German Grand Prix |
E1037495
|
entity |
| Predicate | featuredCarNickname |
P55902
|
FINISHED |
| Object | Silver Arrows |
E80446
|
NE 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: Silver Arrows | Statement: [1936 German Grand Prix, featuredCarNickname, Silver Arrows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuredCarNickname Context triple: [1936 German Grand Prix, featuredCarNickname, Silver Arrows]
-
A.
raceCarName
Indicates that a given name is the designated name or title of a specific race car.
-
B.
vehicleNamesTheme
Indicates that the relationship or context involves a theme centered around vehicle names.
-
C.
vehicleName
chosen
Indicates the specific name or designation assigned to a vehicle.
-
D.
notableCar
Indicates that the subject is a car recognized for its significance, prominence, or special interest (e.g., historically, culturally, or technically).
-
E.
vehicleTheme
Indicates that an entity serves as the vehicle or means through which another entity, event, or action is carried out or expressed.
- F. None of above.
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_69f76e1e701c8190a4990d4978ce4fe6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38a4f6c3b88190b435e6b2d1a257ce |
completed | June 22, 2026, 2:59 a.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.