Triple
T16342706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agua Volcano |
E396845
|
entity |
| Predicate | nameMeaning |
P453
|
FINISHED |
| Object |
Water Volcano
Water Volcano is a stratovolcano in Guatemala known for its prominent conical shape and proximity to the city of Antigua.
|
E1208078
|
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: Water Volcano | Statement: [Agua Volcano, nameMeaning, Water Volcano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Water Volcano Context triple: [Agua Volcano, nameMeaning, Water Volcano]
-
A.
Lavapura
Lavapura is the historical name for Lopburi, an ancient city in central Thailand known for its Khmer-era ruins and long-standing cultural significance.
-
B.
Lava
Lava is a legendary prince in the Hindu epic Ramayana, known as one of the twin sons of Rama and Sita.
-
C.
Lava
Lava is a surname most notably borne by American film and television composer William Lava, known for his work on numerous Warner Bros. cartoons and Westerns.
-
D.
Lava
Lava is a Pixar animated musical short film that tells a romantic, volcano-themed love story through a Hawaiian-inspired song.
-
E.
Lava
"Lava" is a nonfiction book by Andrea Warren that explores the science, danger, and human stories surrounding volcanic eruptions.
- 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: Water Volcano Triple: [Agua Volcano, nameMeaning, Water Volcano]
Generated description
Water Volcano is a stratovolcano in Guatemala known for its prominent conical shape and proximity to the city of Antigua.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Water Volcano Target entity description: Water Volcano is a stratovolcano in Guatemala known for its prominent conical shape and proximity to the city of Antigua.
-
A.
Lavapura
Lavapura is the historical name for Lopburi, an ancient city in central Thailand known for its Khmer-era ruins and long-standing cultural significance.
-
B.
Lava
Lava is a legendary prince in the Hindu epic Ramayana, known as one of the twin sons of Rama and Sita.
-
C.
Lava
Lava is a small hill town in West Bengal, India, known as a gateway to the Neora Valley National Park and for its cool climate and forested surroundings.
-
D.
Lava
Lava is a surname most notably borne by American film and television composer William Lava, known for his work on numerous Warner Bros. cartoons and Westerns.
-
E.
Lava
Lava is a Pixar animated musical short film that tells a romantic, volcano-themed love story through a Hawaiian-inspired song.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2da0b88d081908a99cafa8e0ae5db |
completed | April 18, 2026, 1:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002dadcaa48190865cec201cde47e3 |
completed | May 10, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_6a002e8094e08190b168d6ae5e9de604 |
completed | May 10, 2026, 7:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a002f4c23e481909bf11d7329e0bd6f |
completed | May 10, 2026, 7:10 a.m. |
Created at: April 10, 2026, 5:07 a.m.