Triple
T472102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SEPTA bus routes |
E8579
|
entity |
| Predicate | languageOfServiceInformation |
P6898
|
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: [SEPTA bus routes, languageOfServiceInformation, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfServiceInformation Context triple: [SEPTA bus routes, languageOfServiceInformation, English]
-
A.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
B.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
C.
languageOfSignage
Indicates the language used on signs or written displays associated with an entity.
-
D.
languageOfOfficialAnnouncements
chosen
Indicates the language used for formal or official public announcements issued by an authority.
-
E.
languageOfRecords
Indicates the language in which the records are written or maintained.
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eff24108819092fdb85019ec4089 |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2edecefb081908331ef8b9edf6636 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.