Triple
T14273113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Lympia |
E353841
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Mont Boron |
E154523
|
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: Mont Boron | Statement: [Port Lympia, adjacentTo, Mont Boron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mont Boron Context triple: [Port Lympia, adjacentTo, Mont Boron]
-
A.
Mont Boron
chosen
Mont Boron is a wooded hill and residential area in Nice, France, known for its panoramic views over the city and the Mediterranean coast.
-
B.
Mount Vardousia
Mount Vardousia is a rugged, high-altitude mountain massif in central Greece known for its dramatic peaks and popular hiking and mountaineering routes.
-
C.
Mount Taron
Mount Taron is the tallest mountain on New Ireland Island in Papua New Guinea, known for its rugged terrain and dense tropical rainforest.
-
D.
Mount Voras
Mount Voras is a prominent mountain on the border between Greece and North Macedonia, known for its ski resort and scenic alpine landscapes.
-
E.
Mount Bross
Mount Bross is a high mountain summit in Colorado’s Mosquito Range, known as one of the state’s 14,000-foot peaks and a popular destination for hikers and peak-baggers.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de65811d7c8190b075909a6570d415 |
completed | April 14, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd326a5aec8190b139a0c49fd43705 |
completed | May 8, 2026, 12:46 a.m. |
Created at: April 10, 2026, 1:10 a.m.