Triple
T8095197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stuttgart region |
E188965
|
entity |
| Predicate | hasEconomicSpecialization |
P47951
|
FINISHED |
| Object | automotive industry |
—
|
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 industry | Statement: [Stuttgart region, hasEconomicSpecialization, automotive industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEconomicSpecialization Context triple: [Stuttgart region, hasEconomicSpecialization, automotive industry]
-
A.
hasEconomicFocus
chosen
Indicates that an entity is primarily concerned with, oriented toward, or specializing in economic matters, activities, or impacts.
-
B.
hasEconomicRole
Indicates that an entity participates in or fulfills a specific function, position, or responsibility within an economic system or activity.
-
C.
hasEconomyCharacteristic
Indicates that an economy possesses a particular attribute, feature, or quality.
-
D.
hasEconomicOrganization
Indicates that an entity possesses, is associated with, or participates in a specific economic organization or institutional economic structure.
-
E.
hasEconomicPosition
Indicates that an entity holds a particular role, status, or standing within an economic system or structure.
- 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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4291f1d4819098985ac2b20b6c75 |
completed | March 31, 2026, 3:42 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:30 p.m.