Triple
T18860462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biles II (floor exercise, triple-twisting double back) |
E461297
|
entity |
| Predicate | flipCount |
P133199
|
FINISHED |
| Object | two |
—
|
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: two | Statement: [Biles II (floor exercise, triple-twisting double back), flipCount, two]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flipCount Context triple: [Biles II (floor exercise, triple-twisting double back), flipCount, two]
-
A.
movementCount
Indicates the number of times a movement or relocation action has occurred between the related entities.
-
B.
roundCount
Indicates the number of discrete rounds or iterations that have occurred or are allocated within a process, event, or interaction.
-
C.
arrowCount
Indicates the number of arrows associated with or involved in a given entity or interaction.
-
D.
dropCount
Indicates the number of times an entity has been dropped or caused to drop something.
-
E.
lapCountVariant
Indicates a variation or alternative form of a standard lap count used to measure repetitions or circuits in an activity or process.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c060bfc4819092ac591692a6ccd5 |
completed | April 20, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69e48d2166b88190add38de96cedc65c |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49785fd7081909577e90a55df0a35 |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 10, 2026, 11:57 a.m.