Triple
T36007933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Twain’s Mississippi River world |
E1041322
|
entity |
| Predicate | setAlong |
P2409
|
FINISHED |
| Object | Mississippi River |
—
|
NE NERFINISHED |
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: Mississippi River | Statement: [Mark Twain’s Mississippi River world, setAlong, Mississippi River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setAlong Context triple: [Mark Twain’s Mississippi River world, setAlong, Mississippi River]
-
A.
definedAlong
Indicates that one entity is specified, established, or determined in relation to the course, boundary, or extent of another entity.
-
B.
extendsAlongside
Indicates that one entity continues or stretches in a direction parallel and adjacent to another entity over some distance.
-
C.
measuredAlong
Indicates that a measurement is taken or defined with respect to a specific direction, axis, path, or dimension.
-
D.
locatedAlong
chosen
Indicates that one entity is situated adjacent to, or running beside, the length or course of another linear feature (such as a road, river, or railway).
-
E.
passedAlongside
Indicates that one entity moved or traveled next to another entity along the same route or path, maintaining a roughly parallel course.
- 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_69f76e2a02208190aedd1f9025a8b300 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acb1320c81909f62b3c8101ec5a7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.