Triple
T24471604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heavy and Chemical Industrialization era of South Korea |
E617114
|
entity |
| Predicate | majorEnterpriseType |
P124170
|
FINISHED |
| Object | chaebol |
—
|
NE NERFINISHED |
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: chaebol | Statement: [Heavy and Chemical Industrialization era of South Korea, majorEnterpriseType, chaebol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorEnterpriseType Context triple: [Heavy and Chemical Industrialization era of South Korea, majorEnterpriseType, chaebol]
-
A.
typicalEnterprises
Indicates that an entity is a standard or representative example of enterprises within a given context or category.
-
B.
typeOfEnterpriseBuilt
Indicates the specific kind or category of enterprise that has been constructed or established.
-
C.
modernOrganizationType
Indicates that an entity is classified as a contemporary or currently recognized type of organization, specifying its modern organizational form or category.
-
D.
majorCustomer
Indicates that one entity is a primary or high-value customer of another entity, typically contributing a significant portion of business or revenue.
-
E.
hasMajorEmployerType
chosen
Indicates the type or category of major employer associated with an entity.
- 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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29943e9cc81909f1742c778bf3587 |
completed | April 29, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69f287d76c7c81909494f12e606a9149 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:20 a.m.