Triple
T8860616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oromia Region |
E210877
|
entity |
| Predicate | hasMountain |
P10602
|
FINISHED |
| Object |
Mount Batu
Mount Batu is a prominent high peak in Ethiopia’s Bale Mountains, known for its rugged terrain and alpine ecosystems.
|
E762161
|
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 Batu | Statement: [Oromia Region, hasMountain, Mount Batu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Batu Context triple: [Oromia Region, hasMountain, Mount Batu]
-
A.
Mount Batini
Mount Batini is the highest peak on Vanua Levu, Fiji’s second-largest island.
-
B.
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.
-
C.
Mount Batok
Mount Batok is a small, steep-sided volcanic cone in East Java, Indonesia, located near Mount Bromo within the Tengger caldera and known for its striking, photogenic profile.
-
D.
Mount Mulu
Mount Mulu is a prominent limestone mountain in northern Borneo, Malaysia, renowned for its dramatic karst landscapes and extensive cave systems.
-
E.
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.
- 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 Batu Triple: [Oromia Region, hasMountain, Mount Batu]
Generated description
Mount Batu is a prominent high peak in Ethiopia’s Bale Mountains, known for its rugged terrain and alpine ecosystems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mount Batu Target entity description: Mount Batu is a prominent high peak in Ethiopia’s Bale Mountains, known for its rugged terrain and alpine ecosystems.
-
A.
Mount Batini
Mount Batini is the highest peak on Vanua Levu, Fiji’s second-largest island.
-
B.
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.
-
C.
Mount Batok
Mount Batok is a small, steep-sided volcanic cone in East Java, Indonesia, located near Mount Bromo within the Tengger caldera and known for its striking, photogenic profile.
-
D.
Mount Mulu
Mount Mulu is a prominent limestone mountain in northern Borneo, Malaysia, renowned for its dramatic karst landscapes and extensive cave systems.
-
E.
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.
- 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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60e712d08190bfb1c4ba3acaea90 |
completed | April 1, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfa0b94f5481909902b5fa405a502f |
completed | April 3, 2026, 11:12 a.m. |
| NEDg | Description generation | batch_69cfa1714b4081909035c9b15c82c1be |
completed | April 3, 2026, 11:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfa24be80481909e2b575f99cd1dc4 |
completed | April 3, 2026, 11:19 a.m. |
Created at: March 30, 2026, 6:50 p.m.