Triple
T6649574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Exor N.V. |
E150785
|
entity |
| Predicate | hasMajorInvestmentInSector |
P17330
|
FINISHED |
| Object | automotive |
—
|
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: automotive | Statement: [Exor N.V., hasMajorInvestmentInSector, automotive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorInvestmentInSector Context triple: [Exor N.V., hasMajorInvestmentInSector, automotive]
-
A.
investsIn
chosen
Indicates that one entity allocates resources, typically money or capital, into another entity with the expectation of future returns or benefits.
-
B.
hasInvestmentTheme
Indicates that an investment, fund, or financial product is associated with a particular overarching theme or strategic focus (such as technology, sustainability, or healthcare).
-
C.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
D.
sectorInfluence
Indicates the degree to which one sector affects, shapes, or exerts control over another sector or over outcomes within that sector.
-
E.
notableSector
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
- 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_69c687f2c9508190a60b9aad31d3f358 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad04d66c8190926ffcbff372643b |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:01 p.m.