Triple
T30714785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NM-02 trains |
E781992
|
entity |
| Predicate | operatorLanguageContext |
P91220
|
FINISHED |
| Object | Spanish-speaking transit system |
—
|
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: Spanish-speaking transit system | Statement: [NM-02 trains, operatorLanguageContext, Spanish-speaking transit system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatorLanguageContext Context triple: [NM-02 trains, operatorLanguageContext, Spanish-speaking transit system]
-
A.
operatorContext
Indicates the situational or environmental conditions under which an operator performs an action or maintains a relationship with another entity.
-
B.
languageOfOperator
chosen
Indicates that a particular language is used by, or associated with, a given operator in performing its functions or services.
-
C.
languageOfOperation
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
-
D.
hasLanguageContext
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
E.
languageOfInvocation
Indicates the language used to formulate or express a particular invocation, request, or call.
- 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_69f224acd24481908ed5f96f0d69b5dd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff7595c9bc8190982c6e6e07a0c78f |
completed | May 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69ff715432a88190a25670d26614bde2 |
completed | May 9, 2026, 5:39 p.m. |
Created at: April 29, 2026, 8:35 p.m.