Triple
T15427867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pascagoula |
E369557
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Moss Point |
E976864
|
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: Moss Point | Statement: [Pascagoula, borderedBy, Moss Point]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moss Point Context triple: [Pascagoula, borderedBy, Moss Point]
-
A.
Moss Point
chosen
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.
-
B.
Pascagoula
Pascagoula is a coastal city in southeastern Mississippi known for its major shipbuilding industry and location along the Gulf of Mexico.
-
C.
Biloxi
Biloxi is a coastal Mississippi city known for its beaches, casinos, and seafood industry along the Gulf of Mexico.
-
D.
Grand Bay
Grand Bay is the main town and administrative center of Saint Patrick Parish on the Caribbean island nation of Dominica.
-
E.
Gulfport, Mississippi
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.
- 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ec31f4881908b26ff7c381d7bc9 |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002d966ffc8190aa0d9d3abf8ad593 |
completed | May 10, 2026, 7:02 a.m. |
Created at: April 10, 2026, 3:20 a.m.