Triple
T21631461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | monobob |
E533839
|
entity |
| Predicate | sledType |
P145312
|
FINISHED |
| Object | standardized sled design in many competitions |
—
|
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: standardized sled design in many competitions | Statement: [monobob, sledType, standardized sled design in many competitions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sledType Context triple: [monobob, sledType, standardized sled design in many competitions]
-
A.
lugeType
Indicates the specific category or style of luge associated with an entity (e.g., type of luge event, sled, or discipline).
-
B.
hasSnowType
Indicates that something possesses or is characterized by a particular type or category of snow.
-
C.
spurType
Indicates the specific kind or category of spur associated with or used by an entity.
-
D.
wheelType
Indicates the specific kind or category of wheel associated with an entity.
-
E.
trekType
Indicates the specific category or style of trekking activity associated with an entity.
- F. None of above. chosen
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_69e0c465ae7481908577b7209fdb2a77 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef5217952c8190910c2103fb4a27d9 |
completed | April 27, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69cb4bcbc8190a4fc2d508df107be |
completed | April 20, 2026, 9:37 p.m. |
Created at: April 16, 2026, 6:34 p.m.