Triple
T8932884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bong County |
E212699
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Lofa County |
E194997
|
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: Lofa County | Statement: [Bong County, borderedBy, Lofa County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lofa County Context triple: [Bong County, borderedBy, Lofa County]
-
A.
Lofa County
chosen
Lofa County is a region in northern Liberia known for its ethnic diversity, agricultural production, and its significant role in the country's civil conflicts.
-
B.
Antu County
Antu County is a county-level administrative region in northeastern China's Jilin Province, known for its location within the Yanbian Korean Autonomous Prefecture and proximity to the Changbai Mountains.
-
C.
Luan County
Luan County is an administrative county under the jurisdiction of Tangshan City in Hebei Province, northeastern China.
-
D.
Murang'a County
Murang'a County is an administrative region in central Kenya known for its fertile highlands, tea and coffee farming, and as part of the former Central Province.
-
E.
Gbarpolu County
Gbarpolu County is an administrative region in northwestern Liberia known for its dense forests, mining activities, and predominantly rural communities.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc668e5c108190b08f9cd6b4fd4a8b |
completed | April 1, 2026, 12:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc1d965cc8190bad0a990df318698 |
completed | April 3, 2026, 1:34 p.m. |
Created at: March 30, 2026, 6:57 p.m.