Triple
T1359963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Guiana |
E29075
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Cayenne |
E161877
|
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: Cayenne | Statement: [French Guiana, hasCity, Cayenne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cayenne Context triple: [French Guiana, hasCity, Cayenne]
-
A.
Cayenne
chosen
Cayenne is the principal city and administrative center of French Guiana, located on the Atlantic coast in northeastern South America.
-
B.
Canela
Canela is a coastal rural municipality in Chile’s Coquimbo Region, known for its small agricultural communities and semi-arid landscapes.
-
C.
San Blas
San Blas is a coastal town and port in the Mexican state of Nayarit, known for its beaches, fishing, and nearby mangrove and bird-filled wetlands.
-
D.
San Felipe
San Felipe is a historic city in central Chile known for its agricultural surroundings and role as a commercial and administrative center in the Aconcagua Valley.
-
E.
Mocorito
Mocorito is a historic town and municipality in the Mexican state of Sinaloa, known for its colonial architecture and cultural traditions.
- 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2b156b081909c99ada70a969fc0 |
completed | March 1, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad08a7ed5c8190b9f99a6f4524eae8 |
completed | March 8, 2026, 5:27 a.m. |
Created at: March 1, 2026, 7:56 p.m.