Triple
T7325358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volacom |
E168857
|
entity |
| Predicate | hasNotableFounderExpertise |
P34789
|
FINISHED |
| Object | battery technology |
—
|
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: battery technology | Statement: [Volacom, hasNotableFounderExpertise, battery technology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableFounderExpertise Context triple: [Volacom, hasNotableFounderExpertise, battery technology]
-
A.
hasNotableFounder
Indicates that an entity was founded or established by a person or organization considered especially significant or noteworthy.
-
B.
notableFounderTeam
Indicates that the entity has a founding team whose members are particularly distinguished, prominent, or otherwise noteworthy.
-
C.
hasNotableFacultyAlumnus
Indicates that an individual is a distinguished former student who is recognized as notable faculty at a given institution.
-
D.
hasTypicalFounder
Indicates that an entity is commonly or characteristically founded or established by a particular type of founder.
-
E.
hasFounderBackground
chosen
Indicates that an entity has a founder whose background (such as experience, education, or prior roles) matches a specified profile or characteristic.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f04993408190b73fb46d83a632d5 |
completed | March 27, 2026, 9:02 p.m. |
| PD | Predicate disambiguation | batch_69c6e77230048190b2c29ca6b3a65b8e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:03 p.m.