Triple
T8774060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French A8 motorway |
E208532
|
entity |
| Predicate | hasSectionWith |
P85325
|
FINISHED |
| Object | heavy summer congestion |
—
|
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: heavy summer congestion | Statement: [French A8 motorway, hasSectionWith, heavy summer congestion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionWith Context triple: [French A8 motorway, hasSectionWith, heavy summer congestion]
-
A.
hasSectionIn
Indicates that one entity contains or includes another entity as a section or subdivision within it.
-
B.
hasSectionOn
Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
-
C.
hasSect
Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
-
D.
hasSectionRole
Indicates that an entity holds a specific role or function within a particular section or subdivision of a larger structure or context.
-
E.
hasOptionalSection
Indicates that an entity includes a section or component that is not mandatory and may or may not be present.
- 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_69ca835edb4481909b4aafb616dc5eb7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f2ef3288190988bd69e8a02e741 |
completed | March 31, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:41 p.m.