Triple
T16679920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supai Post Office |
E405311
|
entity |
| Predicate | transportFrequency |
P20359
|
FINISHED |
| Object | mule trains typically operate several times per week |
—
|
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: mule trains typically operate several times per week | Statement: [Supai Post Office, transportFrequency, mule trains typically operate several times per week]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportFrequency Context triple: [Supai Post Office, transportFrequency, mule trains typically operate several times per week]
-
A.
transitFrequencyApprox
chosen
Indicates an approximate rate or regularity with which a transit event or service occurs between entities.
-
B.
transportPattern
Indicates a recurring or characteristic way in which transportation is carried out between entities, such as typical routes, modes, or schedules.
-
C.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
D.
passesUsedForTransportation
Indicates that the passes are utilized as a means or instrument for transporting people or goods.
-
E.
transportReliability
Indicates how consistently and dependably a transport service or system performs as expected over time.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6e74ec81909ea95c3e4b0113ab |
completed | April 18, 2026, 12:47 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:19 a.m.