Triple
T741740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T-MEC |
E15256
|
entity |
| Predicate | hasProvision |
P11051
|
FINISHED |
| Object | automotive rules of origin |
—
|
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 rules of origin | Statement: [T-MEC, hasProvision, automotive rules of origin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProvision Context triple: [T-MEC, hasProvision, automotive rules of origin]
-
A.
hasProvisionOn
chosen
Indicates that one entity contains, specifies, or includes a particular provision, clause, or stipulation concerning another entity or subject.
-
B.
hasPlan
Indicates that an entity possesses or is associated with a specific plan or course of action.
-
C.
hasCP
Indicates that an entity possesses, is associated with, or is characterized by a specific CP (such as a control point, contact person, or configuration parameter), depending on the domain context.
-
D.
hasPar
Indicates a relationship where one entity has another entity as its parent.
-
E.
hasProportion
Indicates that one entity stands in a specified ratio, fraction, or relative share to another entity or whole.
- 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a60e286c81908787a41cf9b9f150 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fdaaf48190985f62acfc069508 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.