Triple
T4302895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Redonda |
E99881
|
entity |
| Predicate | nearbyCountry |
P7310
|
FINISHED |
| Object | Montserrat |
E17737
|
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: Montserrat | Statement: [Redonda, nearbyCountry, Montserrat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montserrat Context triple: [Redonda, nearbyCountry, Montserrat]
-
A.
Montserrat
chosen
Montserrat is a small Caribbean island and British Overseas Territory known for its volcanic activity and lush, mountainous landscape.
-
B.
Serra
Serra is a Spanish surname most famously associated with Junípero Serra, the 18th-century Franciscan friar who founded several missions in what is now California.
-
C.
Morne la Selle
Morne la Selle is the highest mountain in Haiti, located in the southern part of the country.
-
D.
Mount Aigaleo
Mount Aigaleo is a low mountain range in the Attica region of Greece, west of Athens, known for its historical and strategic significance overlooking the ancient battlefield of Salamis.
-
E.
Mount Pico
Mount Pico is a prominent stratovolcano on Pico Island in the Azores and the highest peak in Portugal.
- 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_69b345528ebc8190b5abc7e95094792d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350b66450819089c9ff6ff9f045e5 |
completed | March 12, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c7507f1081909cf737dff00542d9 |
completed | March 14, 2026, 8:38 p.m. |
Created at: March 12, 2026, 11:08 p.m.