Triple
T9914345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Dorian |
E185829
|
entity |
| Predicate | affectedCountry |
P8692
|
FINISHED |
| Object | Barbados |
E11557
|
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: Barbados | Statement: [Hurricane Dorian, affectedCountry, Barbados]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barbados Context triple: [Hurricane Dorian, affectedCountry, Barbados]
-
A.
Barbados
chosen
Barbados is an island country in the Caribbean known for its beaches, coral reefs, and status as a popular tourist destination.
-
B.
Antigua and Barbuda
Antigua and Barbuda is a small Caribbean island nation known for its tourism-driven economy, coral reefs, and numerous white-sand beaches.
-
C.
Saint Vincent and the Grenadines
Saint Vincent and the Grenadines is a small Caribbean island nation known for its volcanic main island, numerous smaller Grenadine islands, and tourism centered on sailing and beaches.
-
D.
Trinidad and Tobago
Trinidad and Tobago is a twin-island Caribbean nation known for its rich cultural diversity, vibrant Carnival celebrations, and significant oil and natural gas resources.
-
E.
Saint Lucia
Saint Lucia is a small Caribbean island nation known for its dramatic Piton mountains, lush rainforests, and popular beach resorts.
- 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_69ca829b45f481909040f7b99a1976ed |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb53ba1ac8190ba655133b81596d7 |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b5c126c081909a072034fde64a04 |
completed | April 5, 2026, 7:19 p.m. |
Created at: March 30, 2026, 8:41 p.m.