Triple
T15219169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abucay |
E363715
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Mount Natib |
E86860
|
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: Mount Natib | Statement: [Abucay, locatedNear, Mount Natib]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Natib Context triple: [Abucay, locatedNear, Mount Natib]
-
A.
Mount Natib
chosen
Mount Natib is a prominent stratovolcano and one of the highest peaks in the Bataan Peninsula of the Philippines, known for its forested slopes and surrounding protected landscape.
-
B.
Mount Batu
Mount Batu is a prominent high peak in Ethiopia’s Bale Mountains, known for its rugged terrain and alpine ecosystems.
-
C.
Mount Welirang
Mount Welirang is an active stratovolcano in East Java, Indonesia, known for its sulfur mining and frequent fumarolic activity.
-
D.
Mount Batini
Mount Batini is the highest peak on Vanua Levu, Fiji’s second-largest island.
-
E.
Mount Mulu
Mount Mulu is a prominent limestone mountain in northern Borneo, Malaysia, renowned for its dramatic karst landscapes and extensive cave systems.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007709d3881908384f0fe1e0218d0 |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed345d58c81908a8fd182c0fe7c15 |
completed | May 9, 2026, 6:25 a.m. |
Created at: April 10, 2026, 3:11 a.m.