Triple
T4283604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanua Levu |
E97212
|
entity |
| Predicate | highestPoint |
P210
|
FINISHED |
| Object |
Mount Batini
Mount Batini is the highest peak on Vanua Levu, Fiji’s second-largest island.
|
E426765
|
NE FINISHED |
How this triple was built (4 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 Batini | Statement: [Vanua Levu, highestPoint, Mount Batini]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Batini Context triple: [Vanua Levu, highestPoint, Mount Batini]
-
A.
Mount Natib
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 Wanggameti
Mount Wanggameti is the tallest mountain on the Indonesian island of Sumba, known for its forested slopes and biodiversity within protected conservation areas.
-
C.
Mount Welirang
Mount Welirang is an active stratovolcano in East Java, Indonesia, known for its sulfur mining and frequent fumarolic activity.
-
D.
Mount Talang
Mount Talang is an active stratovolcano in Indonesia known for its frequent eruptions and location near the city of Padang in West Sumatra.
-
E.
Mount Loilaeng
Mount Loilaeng is a prominent peak in eastern Myanmar, recognized as the highest mountain in the Shan Hills range.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mount Batini Triple: [Vanua Levu, highestPoint, Mount Batini]
Generated description
Mount Batini is the highest peak on Vanua Levu, Fiji’s second-largest island.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mount Batini Target entity description: Mount Batini is the highest peak on Vanua Levu, Fiji’s second-largest island.
-
A.
Mount Natib
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 Wanggameti
Mount Wanggameti is the tallest mountain on the Indonesian island of Sumba, known for its forested slopes and biodiversity within protected conservation areas.
-
C.
Mount Welirang
Mount Welirang is an active stratovolcano in East Java, Indonesia, known for its sulfur mining and frequent fumarolic activity.
-
D.
Mount Talang
Mount Talang is an active stratovolcano in Indonesia known for its frequent eruptions and location near the city of Padang in West Sumatra.
-
E.
Mount Loilaeng
Mount Loilaeng is a prominent peak in eastern Myanmar, recognized as the highest mountain in the Shan Hills range.
- F. None of above. chosen
Provenance (5 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3503a84548190989a96d1a30d6ef7 |
completed | March 12, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7c2023c8190a2359f8cabcecd2c |
completed | March 14, 2026, 7:32 p.m. |
| NEDg | Description generation | batch_69b5b94471588190a27e7df972f072b1 |
completed | March 14, 2026, 7:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5ba4262b481908378f7ebdc9a7c9c |
completed | March 14, 2026, 7:42 p.m. |
Created at: March 12, 2026, 11:07 p.m.