Triple
T1622829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palermo FC |
E35070
|
entity |
| Predicate | hasYouthSector |
P6626
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Palermo FC, hasYouthSector, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasYouthSector Context triple: [Palermo FC, hasYouthSector, yes]
-
A.
hasYouthProgram
chosen
Indicates that an entity offers or is associated with an organized program or set of activities specifically designed for young people.
-
B.
youthWing
Indicates that one organization serves as the youth or junior wing of another organization, typically representing younger members aligned with the parent body.
-
C.
hasStudentOrganization
Indicates that an entity (such as an institution or department) is associated with or hosts a particular student organization.
-
D.
hasVolunteerProgram
Indicates that an organization or entity offers an organized program through which individuals can volunteer their time or services.
-
E.
hasEducationalServiceArea
Indicates that an entity (such as an educational institution or authority) is responsible for providing educational services within a specified geographic area.
- 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_69a886023194819080a3fccd6e325d0e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf4a0ef748190ae52b9656474c0ef |
completed | March 6, 2026, 3:37 p.m. |
| PD | Predicate disambiguation | batch_69a907c731808190a1d998155041b3c1 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.