Triple
T7092154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminus, Georgia |
E165220
|
entity |
| Predicate | laterKnownAs |
P65
|
FINISHED |
| Object | Marthasville |
E16951
|
NE 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: Marthasville | Statement: [Terminus, Georgia, laterKnownAs, Marthasville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marthasville Context triple: [Terminus, Georgia, laterKnownAs, Marthasville]
-
A.
Marthasville
chosen
Marthasville was the former name of the city now known as Atlanta, Georgia, during its early 19th-century development as a railroad terminus.
-
B.
Stewarttown
Stewarttown is a small community located within the town of Halton Hills in Ontario, Canada.
-
C.
Yatesville
Yatesville is a small town located in the U.S. state of Georgia.
-
D.
Slatersville
Slatersville is a historic village in North Smithfield, Rhode Island, known as one of America’s first planned mill villages centered around early textile manufacturing.
-
E.
Luthersville
Luthersville is a small rural city in Meriwether County, Georgia, known for its quiet residential character and location in west-central Georgia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6887e8c10819091cee237560d32da |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e53132288190b6da361d9c7218ab |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79c960484819098228cebccb8c935 |
completed | March 28, 2026, 9:17 a.m. |
Created at: March 27, 2026, 2:41 p.m.