Triple
T1053839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Rinjani |
E22756
|
entity |
| Predicate | hasNearbyTown |
P3883
|
FINISHED |
| Object | Senaru |
E124636
|
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: Senaru | Statement: [Mount Rinjani, hasNearbyTown, Senaru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Senaru Context triple: [Mount Rinjani, hasNearbyTown, Senaru]
-
A.
Senaru
chosen
Senaru is a traditional mountain village on the island of Lombok in Indonesia, known as a popular gateway for treks to Mount Rinjani and for its scenic waterfalls and Sasak culture.
-
B.
Tianeti
Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
-
C.
Canazei
Canazei is a mountain village and ski resort in the Dolomites of northern Italy, known for winter sports and alpine tourism.
-
D.
Mella
Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
-
E.
Evessa
Evessa is a professional basketball team based in Osaka, Japan, competing in the B.League.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8d669448190955507e2e4975b9f |
completed | March 1, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4c1b4c3481909ec58291dc9cc32f |
completed | March 7, 2026, 4:02 p.m. |
Created at: March 1, 2026, 7:42 p.m.