Triple
T38209551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toomsuba, Mississippi |
E1009299
|
entity |
| Predicate | adjacentToStateLine |
P13917
|
FINISHED |
| Object | Alabama state line |
—
|
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: Alabama state line | Statement: [Toomsuba, Mississippi, adjacentToStateLine, Alabama state line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentToStateLine Context triple: [Toomsuba, Mississippi, adjacentToStateLine, Alabama state line]
-
A.
hasNearbyStateLine
chosen
Indicates that one location is situated close to the boundary line of a neighboring state.
-
B.
adjacentCityOnLine
Indicates that one city is directly next to another city along the same transportation line or route.
-
C.
isAdjacentTo
Indicates that one entity is directly next to or bordering another without anything of the same type in between.
-
D.
hasAdjacentStationOnBorderlandsLine
Indicates that one station is directly next to another station along the Borderlands Line.
-
E.
nearInternationalBoundary
Indicates that one entity is located close to an international boundary separating two or more countries.
- 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_69f76dc94fcc8190bd2f55e81f9d6527 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: May 3, 2026, 4:30 p.m.