Triple
T6675267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messerschmitt Me 209 V1 |
E151833
|
entity |
| Predicate | recordCategory |
P44262
|
FINISHED |
| Object | world speed record over a 3 km course |
—
|
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: world speed record over a 3 km course | Statement: [Messerschmitt Me 209 V1, recordCategory, world speed record over a 3 km course]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordCategory Context triple: [Messerschmitt Me 209 V1, recordCategory, world speed record over a 3 km course]
-
A.
recordsType
Indicates that one entity documents, stores, or keeps an official account of a particular type or category of information, event, or item.
-
B.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
C.
notableRecordCategory
chosen
Indicates that an entity is notably associated with a particular category of records or record-related achievements.
-
D.
canonicalCategory
Indicates that an entity is assigned to its primary or standard category within a classification system.
-
E.
recordingType
Indicates the specific kind or category of recording associated with an entity (e.g., audio, video, live, studio, etc.).
- 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c0aa8c5c8190a302b261f11b70cb |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0b6d00819086205b8ce30dd045 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:03 p.m.