Triple
T7252771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wooden Wonder |
E157643
|
entity |
| Predicate | appliesToVariantFamily |
P75571
|
FINISHED |
| Object | Mosquito bomber variants |
—
|
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: Mosquito bomber variants | Statement: [Wooden Wonder, appliesToVariantFamily, Mosquito bomber variants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToVariantFamily Context triple: [Wooden Wonder, appliesToVariantFamily, Mosquito bomber variants]
-
A.
hasVariantFamily
Indicates that one entity is related to another as a different version, type, or family variant of it.
-
B.
appliesToFeature
Indicates that something (such as a rule, constraint, or configuration) is relevant to, or governs, a specific feature.
-
C.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
D.
supportsModelVariant
Indicates that one entity is capable of operating with, being compatible with, or otherwise accommodating a specific variant of a model.
-
E.
appliesToProductType
Indicates that something (such as a rule, offer, or condition) is relevant or applicable specifically to a certain type or category of product.
- 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_69c6882d81d4819085f7ff862951ee4f |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea9d41908190bb76c6a5b9d5b1a2 |
completed | March 27, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69c6e7666ffc81908bf643d8257e6337 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6e889854481908c765ce2107f2d3a |
completed | March 27, 2026, 8:28 p.m. |
Created at: March 27, 2026, 2:56 p.m.