Triple
T13925245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort McClellan |
E334846
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Anniston |
E66579
|
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: Anniston | Statement: [Fort McClellan, nearbyCity, Anniston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anniston Context triple: [Fort McClellan, nearbyCity, Anniston]
-
A.
Anniston, Alabama
chosen
Anniston, Alabama is a small city in northeastern Alabama known historically as a planned industrial community and gateway to the nearby Appalachian foothills.
-
B.
Phenix City
Phenix City is a city in eastern Alabama located along the Chattahoochee River, directly across from Columbus, Georgia.
-
C.
Demopolis
Demopolis is a small historic city in western Alabama known for its antebellum architecture and location at the confluence of the Tombigbee and Black Warrior rivers.
-
D.
Tuscumbia
Tuscumbia is a small historic city in northwestern Alabama, best known as the birthplace of Helen Keller and for its role in the early development of the region.
-
E.
Cullman
Cullman is a small city in north-central Alabama known for its German heritage, historic downtown, and proximity to Smith Lake.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2aa6cd9881908f652538f4613f37 |
completed | April 14, 2026, 11:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8a9eeff48190b8aa9a601574395a |
completed | May 8, 2026, 7:02 a.m. |
Created at: April 9, 2026, 10:16 p.m.