Triple
T4505953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben 10 |
E101331
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Charmcaster
Charmcaster is a recurring villain and powerful magic-wielding sorceress in the Ben 10 animated franchise.
|
E447767
|
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: Charmcaster | Statement: [Ben 10, hasCharacter, Charmcaster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charmcaster Context triple: [Ben 10, hasCharacter, Charmcaster]
-
A.
Warlock
Warlock is a Hearthstone hero class themed around dark magic and demonic powers, often trading its own health for powerful cards and effects.
-
B.
Warlock
"Warlock" is a historical adventure novel by Wilbur Smith set in ancient Egypt, continuing the saga of the master strategist and mage Taita.
-
C.
The Mage
The Mage is a powerful and enigmatic magic-user who aids Arthur with supernatural abilities and guidance in the fantasy film "King Arthur: Legend of the Sword."
-
D.
Magus
Magus is a mysterious spiritual master in Paulo Coelho’s novel "Brida," guiding the protagonist through her journey of self-discovery and magical initiation.
-
E.
Battlemage
Battlemage is the codename for Intel’s planned second-generation Arc discrete graphics architecture, intended to succeed the first-generation Alchemist GPUs.
- 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: Charmcaster Triple: [Ben 10, hasCharacter, Charmcaster]
Generated description
Charmcaster is a recurring villain and powerful magic-wielding sorceress in the Ben 10 animated franchise.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Charmcaster Target entity description: Charmcaster is a recurring villain and powerful magic-wielding sorceress in the Ben 10 animated franchise.
-
A.
Warlock
Warlock is a Hearthstone hero class themed around dark magic and demonic powers, often trading its own health for powerful cards and effects.
-
B.
Warlock
"Warlock" is a historical adventure novel by Wilbur Smith set in ancient Egypt, continuing the saga of the master strategist and mage Taita.
-
C.
The Mage
The Mage is a powerful and enigmatic magic-user who aids Arthur with supernatural abilities and guidance in the fantasy film "King Arthur: Legend of the Sword."
-
D.
Magus
Magus is a mysterious spiritual master in Paulo Coelho’s novel "Brida," guiding the protagonist through her journey of self-discovery and magical initiation.
-
E.
Battlemage
Battlemage is the codename for Intel’s planned second-generation Arc discrete graphics architecture, intended to succeed the first-generation Alchemist GPUs.
- 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_69bd43d175248190894dc58b5b395c26 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56ff78748190bb667e70c69dc817 |
completed | March 20, 2026, 2:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd6f9961ac8190954b2d352d2319fb |
completed | March 20, 2026, 4:02 p.m. |
| NEDg | Description generation | batch_69bd705e0e848190a73e7ddb569f0e37 |
completed | March 20, 2026, 4:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bd71b41664819091bd4f75d4634943 |
completed | March 20, 2026, 4:11 p.m. |
Created at: March 20, 2026, 1:01 p.m.