Triple
T637233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese Culture Center of San Francisco |
E16650
|
entity |
| Predicate | languageOfPrograms |
P4197
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Chinese Culture Center of San Francisco, languageOfPrograms, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfPrograms Context triple: [Chinese Culture Center of San Francisco, languageOfPrograms, English]
-
A.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
B.
usedByProgrammingLanguages
Indicates that something (such as a tool, library, paradigm, or feature) is employed or utilized by one or more programming languages.
-
C.
languageName
Indicates the specific name assigned to a language in the relationship.
-
D.
programmingIncludes
Indicates that one programming-related entity contains, incorporates, or makes use of another as a part, feature, or component.
-
E.
languageOfOperation
chosen
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ee7fdbc8190858e42bb1bfdb3ff |
completed | March 1, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69a49d0483908190a5ec42a7403c258e |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.