Triple
T6051452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Savannah Campaign |
E134802
|
entity |
| Predicate | capturedCity |
P8411
|
FINISHED |
| Object | Savannah |
E49314
|
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: Savannah | Statement: [Savannah Campaign, capturedCity, Savannah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Savannah Context triple: [Savannah Campaign, capturedCity, Savannah]
-
A.
Savannah
chosen
Savannah is a historic coastal city in the U.S. state of Georgia, renowned for its well-preserved architecture, cobblestone squares, and rich Southern cultural heritage.
-
B.
Savannah
Savannah is a residential district and one of the main suburban communities on Grand Cayman in the Cayman Islands.
-
C.
Savannah metropolitan area
The Savannah metropolitan area is a coastal urban region in southeastern Georgia centered on the historic port city of Savannah, known for its tourism, logistics, and cultural heritage.
-
D.
Aiken
Aiken is a variant spelling of the surname Aitken, which is of Scottish origin.
-
E.
Marion
Marion is a given name used for people of any gender in various cultures, often as a variant of Mary or Marian.
- 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_69c00877b6d4819096b0e163728b73a3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056f802988190aafdb7cbb087c828 |
completed | March 22, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1357027388190beef9b9d9f5e37f6 |
completed | March 23, 2026, 12:43 p.m. |
Created at: March 22, 2026, 4:09 p.m.