Triple
T3088437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slinky Dog Dash |
E64429
|
entity |
| Predicate | inversionCount |
P41575
|
FINISHED |
| Object | 0 |
—
|
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: 0 | Statement: [Slinky Dog Dash, inversionCount, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inversionCount Context triple: [Slinky Dog Dash, inversionCount, 0]
-
A.
inversions
Indicates a relationship where the usual order, position, or hierarchy between elements is reversed or turned upside down.
-
B.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
C.
count
chosen
Indicates the numerical quantity or total number of instances of a specified entity or event.
-
D.
movementCount
Indicates the number of times a movement or relocation action has occurred between the related entities.
-
E.
numberOfMovements
Indicates the total count of distinct movements or motion events associated with the given entity or context.
- 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_69ad857c97d88190b26f9b1c90839c77 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada20b99a4819090c3d3e08ed556ad |
completed | March 8, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69ad9ded78f881908be6fc0fb7c35764 |
completed | March 8, 2026, 4:03 p.m. |
Created at: March 8, 2026, 3:03 p.m.