Triple
T21184184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simbirsk |
E522034
|
entity |
| Predicate | transportRoleHistorical |
P7949
|
FINISHED |
| Object | river port on the Volga |
—
|
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: river port on the Volga | Statement: [Simbirsk, transportRoleHistorical, river port on the Volga]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportRoleHistorical Context triple: [Simbirsk, transportRoleHistorical, river port on the Volga]
-
A.
transportModeHistorical
Indicates the mode of transportation that was historically used in a given movement, route, or transport event.
-
B.
historicalTraction
Indicates that the subject has demonstrated sustained relevance, influence, or effectiveness over a significant period of time.
-
C.
transportRole
chosen
Indicates that an entity participates in a transportation process with a specific functional role (e.g., carrier, passenger, cargo, or operator).
-
D.
transportationRole
Indicates a role or function that an entity has specifically in the context of providing, operating, or supporting transportation.
-
E.
historicalDriver
Indicates that an entity served as a driver of or significantly contributed to another entity in the past.
- 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_69e0b50ef1d48190b063aa342667df22 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e730205ce88190b0bb33003295d6e7 |
completed | April 21, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69e5f6027c248190a170a36612bd337e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:05 p.m.