Triple
T17925192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drac à Grenoble |
E448175
|
entity |
| Predicate | watercourseNameLanguage |
P129739
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Drac à Grenoble, watercourseNameLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: watercourseNameLanguage Context triple: [Drac à Grenoble, watercourseNameLanguage, French]
-
A.
watercourseName
Indicates the name assigned to a river, stream, or other flowing body of water in the relationship.
-
B.
watercourseIDCountry
Indicates that a specific watercourse is associated with, located in, or flows through a particular country.
-
C.
watercourseFor
Indicates that one entity serves as the watercourse (such as a river or channel) associated with, carrying, or draining another entity.
-
D.
watershedName
Indicates the name assigned to the watershed with which an entity is associated.
-
E.
watercourseFeature
Indicates that a feature is a physical characteristic or component associated with a watercourse (such as a river, stream, or canal).
- 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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a54cf8188190b9bd676443418c23 |
completed | April 19, 2026, 9:50 a.m. |
| PD | Predicate disambiguation | batch_69e3f8e713d481908b4a126258c18b63 |
completed | April 18, 2026, 9:34 p.m. |
| PDg | Predicate description generation | batch_69e42d8d68288190a05dc5d7803cf823 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:20 a.m.