Triple
T29872115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nintendo Switch Sports |
E758616
|
entity |
| Predicate | legStrapUsedFor |
P167691
|
FINISHED |
| Object | soccer shoot-out mode |
—
|
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: soccer shoot-out mode | Statement: [Nintendo Switch Sports, legStrapUsedFor, soccer shoot-out mode]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legStrapUsedFor Context triple: [Nintendo Switch Sports, legStrapUsedFor, soccer shoot-out mode]
-
A.
hasStrapType
Indicates that an item is associated with or equipped with a specific type or style of strap.
-
B.
legCharacteristic
Indicates a characteristic, property, or attribute that specifically pertains to the legs of an entity.
-
C.
usesTwoLeggedTies
Indicates that one entity employs or applies two-legged ties in relation to another entity or context.
-
D.
wearingMethod
Indicates the manner or method by which something is worn or put on.
-
E.
legs
Indicates that an entity possesses legs, specifying the presence or number of leg-like appendages associated with it.
- 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_69f2245d0d7081909e37ee328542bcd7 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f676c6e60c8190925e63bd3221cfd9 |
completed | May 2, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f66ac32b60819092290b2de35988d3 |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66bd123108190b451eb6e23842adb |
completed | May 2, 2026, 9:25 p.m. |
Created at: April 29, 2026, 5:54 p.m.