Triple
T5314025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aktiengesellschaft |
E119100
|
entity |
| Predicate | typicalSectorUse |
P63432
|
FINISHED |
| Object | large enterprises |
—
|
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: large enterprises | Statement: [Aktiengesellschaft, typicalSectorUse, large enterprises]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSectorUse Context triple: [Aktiengesellschaft, typicalSectorUse, large enterprises]
-
A.
partOfUse
Indicates that something functions as a component or constituent within the use or application of something else.
-
B.
typicalUseLocation
Indicates the usual or most common location where an entity is used or operates.
-
C.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
D.
secondaryLandUse
Indicates a secondary or additional way in which a piece of land is used, beyond its primary designated use.
-
E.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
- 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_69bd446b57bc8190a513d2e6c40314f3 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd86f20f008190be7b5848af05f2b8 |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd84534f9c8190bc19d4812060768d |
completed | March 20, 2026, 5:30 p.m. |
| PDg | Predicate description generation | batch_69bd86f0cbfc8190b6665dd9b28d6345 |
completed | March 20, 2026, 5:42 p.m. |
Created at: March 20, 2026, 1:54 p.m.