Triple
T15355801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lego Bionicle |
E367166
|
entity |
| Predicate | hasSetting |
P3538
|
FINISHED |
| Object |
Aqua Magna
Aqua Magna is a fictional ocean-covered planet in the Lego Bionicle universe that serves as one of the primary locations for the story’s events.
|
E1151154
|
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: Aqua Magna | Statement: [Lego Bionicle, hasSetting, Aqua Magna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aqua Magna Context triple: [Lego Bionicle, hasSetting, Aqua Magna]
-
A.
Aqua Tepula
Aqua Tepula was an ancient Roman aqueduct, one of the earlier systems built to supply fresh water to the city of Rome.
-
B.
Aqua Anio Vetus
Aqua Anio Vetus was one of ancient Rome’s earliest major aqueducts, channeling water from the Aniene River to supply the growing city.
-
C.
Aquata
Aquata is one of King Triton’s mermaid daughters and a princess of Atlantica in Disney’s The Little Mermaid franchise.
-
D.
Aquae Cutiliae
Aquae Cutiliae was an ancient Roman spa town in central Italy, renowned for its therapeutic mineral springs and as the place where Emperor Titus died.
-
E.
Brinsea
Brinsea is a small hamlet in North Somerset, England, situated within the civil parish of Congresbury.
- 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: Aqua Magna Triple: [Lego Bionicle, hasSetting, Aqua Magna]
Generated description
Aqua Magna is a fictional ocean-covered planet in the Lego Bionicle universe that serves as one of the primary locations for the story’s events.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aqua Magna Target entity description: Aqua Magna is a fictional ocean-covered planet in the Lego Bionicle universe that serves as one of the primary locations for the story’s events.
-
A.
Aqua Tepula
Aqua Tepula was an ancient Roman aqueduct, one of the earlier systems built to supply fresh water to the city of Rome.
-
B.
Aqua Anio Vetus
Aqua Anio Vetus was one of ancient Rome’s earliest major aqueducts, channeling water from the Aniene River to supply the growing city.
-
C.
Aquata
Aquata is one of King Triton’s mermaid daughters and a princess of Atlantica in Disney’s The Little Mermaid franchise.
-
D.
Aquae Cutiliae
Aquae Cutiliae was an ancient Roman spa town in central Italy, renowned for its therapeutic mineral springs and as the place where Emperor Titus died.
-
E.
Brinsea
Brinsea is a small hamlet in North Somerset, England, situated within the civil parish of Congresbury.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e2c00648190ae2325e1ee58dcfd |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff02012fa48190a108f1ca710ffb15 |
completed | May 9, 2026, 9:44 a.m. |
| NEDg | Description generation | batch_69ff02d0d0188190b6414a52bf8e6e54 |
completed | May 9, 2026, 9:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff037ddf1c8190b7c93c1b3edf33e8 |
completed | May 9, 2026, 9:50 a.m. |
Created at: April 10, 2026, 3:18 a.m.