Triple
T15396806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keesler Air Force Base |
E368196
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Gulfport, Mississippi |
E86848
|
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: Gulfport, Mississippi | Statement: [Keesler Air Force Base, nearbyCity, Gulfport, Mississippi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gulfport, Mississippi Context triple: [Keesler Air Force Base, nearbyCity, Gulfport, Mississippi]
-
A.
Gulfport, Mississippi
chosen
Gulfport, Mississippi is a coastal city on the Gulf of Mexico known for its port, beaches, and role as a major urban center in southern Mississippi.
-
B.
Biloxi
Biloxi is a coastal Mississippi city known for its beaches, casinos, and seafood industry along the Gulf of Mexico.
-
C.
Moss Point
Moss Point is a small coastal city in Jackson County, Mississippi, known for its location along the Pascagoula River and proximity to the Gulf Coast.
-
D.
Pascagoula
Pascagoula is a coastal city in southeastern Mississippi known for its major shipbuilding industry and location along the Gulf of Mexico.
-
E.
Pearl, Mississippi
Pearl, Mississippi is a suburban city in the Jackson metropolitan area known for its residential communities, retail centers, and proximity to major transportation routes.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8c5d40819086622b70edcb6294 |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f7d79348190aba1889a7eb3d7c8 |
completed | May 10, 2026, 6:02 a.m. |
Created at: April 10, 2026, 3:19 a.m.