Triple
T24579991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shenzhen FC |
E608220
|
entity |
| Predicate | hasInternationalStaff |
P156417
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Shenzhen FC, hasInternationalStaff, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInternationalStaff Context triple: [Shenzhen FC, hasInternationalStaff, true]
-
A.
hasInternationalOffice
Indicates that an entity maintains an official office or branch located in a foreign country.
-
B.
hasInternationalManagers
Indicates that an entity has managers who operate or are responsible for activities in multiple countries or international contexts.
-
C.
hasInternationalOrganizationOffice
Indicates that an international organization maintains an official office or physical presence at a given location.
-
D.
hasInternationalStatus
Indicates that an entity holds a recognized status, role, or standing at the international level rather than being limited to a single country or local jurisdiction.
-
E.
hasInternationalStudents
Indicates that an institution or organization includes students who come from countries other than the one in which it is located.
- 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_69e2c4ce89248190ad99e18f0638dfbb |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a97fde9c81909d8de91b6358a015 |
completed | April 30, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f2a6c1f07081908edf0b521767e79b |
completed | April 30, 2026, 12:48 a.m. |
| PDg | Predicate description generation | batch_69f2a846c5bc81909ba50cee483bea91 |
completed | April 30, 2026, 12:54 a.m. |
Created at: April 18, 2026, 2:29 a.m.