Triple
T3945965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maderas Volcano |
E92146
|
entity |
| Predicate | nameMeaning |
P453
|
FINISHED |
| Object |
Maderas
Maderas is a stratovolcano on Ometepe Island in Lake Nicaragua, known for its cloud forest, crater lagoon, and popular hiking trails.
|
E402688
|
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: Maderas | Statement: [Maderas Volcano, nameMeaning, Maderas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maderas Context triple: [Maderas Volcano, nameMeaning, Maderas]
-
A.
Lenswood
Lenswood is a small rural town in South Australia's Adelaide Hills region, known for its cool-climate orchards and scenic vineyards.
-
B.
Sakao
Sakao is an Oceanic language spoken on the island of Espiritu Santo in Vanuatu, noted for its complex phonology and distinctive sound changes.
-
C.
Wood
Wood is a common English surname with historical roots in Britain, often originally referring to someone who lived or worked near a forest.
-
D.
Dalbergia
Dalbergia is a genus of tropical and subtropical trees and shrubs best known for producing valuable hardwoods such as rosewood and kingwood, widely used in fine furniture and musical instruments.
-
E.
Threepwood
Threepwood is the aristocratic family name of the eccentric Blandings Castle clan in P. G. Wodehouse’s comic novels.
- 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: Maderas Triple: [Maderas Volcano, nameMeaning, Maderas]
Generated description
Maderas is a stratovolcano on Ometepe Island in Lake Nicaragua, known for its cloud forest, crater lagoon, and popular hiking trails.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maderas Target entity description: Maderas is a stratovolcano on Ometepe Island in Lake Nicaragua, known for its cloud forest, crater lagoon, and popular hiking trails.
-
A.
Lenswood
Lenswood is a small rural town in South Australia's Adelaide Hills region, known for its cool-climate orchards and scenic vineyards.
-
B.
Sakao
Sakao is an Oceanic language spoken on the island of Espiritu Santo in Vanuatu, noted for its complex phonology and distinctive sound changes.
-
C.
Wood
Wood is a common English surname with historical roots in Britain, often originally referring to someone who lived or worked near a forest.
-
D.
Dalbergia
Dalbergia is a genus of tropical and subtropical trees and shrubs best known for producing valuable hardwoods such as rosewood and kingwood, widely used in fine furniture and musical instruments.
-
E.
Threepwood
Threepwood is the aristocratic family name of the eccentric Blandings Castle clan in P. G. Wodehouse’s comic novels.
- 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_69aed965502c8190904ebad1203a4ae8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef0da13688190aab505c36513e4ab |
completed | March 9, 2026, 4:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5339869fc8190aee0805a8e2deac5 |
completed | March 14, 2026, 10:08 a.m. |
| NEDg | Description generation | batch_69b5376d19bc81909dadce4a2efcd331 |
completed | March 14, 2026, 10:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b538595d2481908812ab03cdb94659 |
completed | March 14, 2026, 10:28 a.m. |
Created at: March 9, 2026, 3:24 p.m.