Triple
T37930099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zoomerang |
E946191
|
entity |
| Predicate | inversionsTakenForwardsAndBackwards |
P189631
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Zoomerang, inversionsTakenForwardsAndBackwards, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inversionsTakenForwardsAndBackwards Context triple: [Zoomerang, inversionsTakenForwardsAndBackwards, yes]
-
A.
inversions
Indicates a relationship where the usual order, position, or hierarchy between elements is reversed or turned upside down.
-
B.
hasInversionCount
Indicates that there is a specific number of pairwise order inversions present in a given sequence or arrangement.
-
C.
numberOfSwapsWorstCase
Indicates the maximum number of swap operations required in the worst-case scenario for a given process or algorithm.
-
D.
isGeneratedByTranspositions
Indicates that one entity is produced from another by applying one or more transposition operations (i.e., swapping positions of elements).
-
E.
reversedChangeOf
Indicates that one entity represents the inverse or opposite direction of a change or transformation described by another 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_69f76ef3b7248190892fb9706423be7c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc7b78f9481909f4f8fc2e3fdcde1 |
completed | May 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69fbbd18c9908190928d274f8731dfa8 |
completed | May 6, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69fbc7b6c2c88190ad4f58980834053c |
completed | May 6, 2026, 10:59 p.m. |
Created at: May 3, 2026, 4:20 p.m.