Triple
T16022192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Río Turia |
E388627
|
entity |
| Predicate | formerCourseUsedFor |
P121399
|
FINISHED |
| Object | urban park in Valencia |
—
|
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: urban park in Valencia | Statement: [Río Turia, formerCourseUsedFor, urban park in Valencia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerCourseUsedFor Context triple: [Río Turia, formerCourseUsedFor, urban park in Valencia]
-
A.
previousCourse
Indicates that one course must be taken before another, typically as a prerequisite or earlier offering in a sequence.
-
B.
usesCourse
Indicates that one entity makes use of, applies, or relies on a particular course in some context or activity.
-
C.
isCourse
Indicates that an entity functions as or qualifies as a course within a given context or system.
-
D.
course
Indicates that an entity is an academic class or unit of instruction offered within an educational program.
-
E.
hasFormerInstitution
Indicates that an entity was previously affiliated with, employed by, or enrolled in a particular institution in the past.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e1826a4f7c8190aba6d4f1075141b0 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e185879c10819080a18e24969b5a6d |
completed | April 17, 2026, 12:57 a.m. |
Created at: April 10, 2026, 4:55 a.m.