Triple
T9248716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makey Makey Classic |
E222262
|
entity |
| Predicate | typicalConductiveObjects |
P87778
|
FINISHED |
| Object | fruit |
—
|
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: fruit | Statement: [Makey Makey Classic, typicalConductiveObjects, fruit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalConductiveObjects Context triple: [Makey Makey Classic, typicalConductiveObjects, fruit]
-
A.
electricalConductivity
Indicates that one entity has the ability to conduct electric current through it, typically quantified as a measure of how easily charge flows within that material or medium.
-
B.
electricalConductivityRank
Indicates the relative position or ranking of an entity based on how well it conducts electricity compared to others.
-
C.
isTypicallyWiredUsing
Indicates that one thing is commonly connected or implemented using a particular type of wiring or cabling.
-
D.
typicalTools
Indicates that the related tools are commonly or characteristically used to perform the associated activity, task, or function.
-
E.
typicalGadgets
Indicates that the associated items are commonly used or standard gadgets typically found or expected in a given context.
- 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_69ca841d2b18819089f9faf5b2c2aec0 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd05f6d62c8190a1e33f1854767b47 |
completed | April 1, 2026, 11:48 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4e79e48190b3200247f4624867 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc95597be081908ece2491dd2f0f74 |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:31 p.m.