Triple
T22920641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirkbi A/S |
E568849
|
entity |
| Predicate | hasInvestmentArea |
P38266
|
FINISHED |
| Object | renewable energy |
—
|
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: renewable energy | Statement: [Kirkbi A/S, hasInvestmentArea, renewable energy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInvestmentArea Context triple: [Kirkbi A/S, hasInvestmentArea, renewable energy]
-
A.
hasInvestmentTheme
chosen
Indicates that an investment, fund, or financial product is associated with a particular overarching theme or strategic focus (such as technology, sustainability, or healthcare).
-
B.
hasImpactArea
Indicates that an entity affects, influences, or has consequences within a specific area, domain, or scope.
-
C.
hasInvestmentStyle
Indicates that an entity (such as a fund or portfolio) follows or is characterized by a particular investment style.
-
D.
investsIn
Indicates that one entity allocates resources, typically money or capital, into another entity with the expectation of future returns or benefits.
-
E.
hasResearchArea
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
- 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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180d40f98819096210c097b47d43b |
completed | April 29, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69ef3b7c5fc081909ac50c5c8569cc19 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:42 p.m.