Triple
T9114393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strange Tales #110 |
E218687
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Wong
Wong is a Marvel Comics character best known as Doctor Strange’s loyal friend, valet, and powerful mystical ally.
|
E779325
|
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: Wong | Statement: [Strange Tales #110, featuresCharacter, Wong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wong Context triple: [Strange Tales #110, featuresCharacter, Wong]
-
A.
Wong
Wong is a common Chinese surname shared by many people of Chinese descent worldwide.
-
B.
Mr. Wong
Mr. Wong is the enigmatic criminal mastermind and primary antagonist in the 1934 mystery film "The Mysterious Mr. Wong."
-
C.
Marcus Wong
Marcus Wong is a Canadian municipal politician who serves as the mayor of West Vancouver, British Columbia.
-
D.
Wong Tai Sin
Wong Tai Sin is a residential and cultural district in northern Kowloon, Hong Kong, best known for its famous Wong Tai Sin Temple and dense public housing estates.
-
E.
Sean Wong
Sean Wong is an American writer and editor known for his contributions to Asian American literature and for co-founding the Before Columbus Foundation, which promotes multicultural literature.
- 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: Wong Triple: [Strange Tales #110, featuresCharacter, Wong]
Generated description
Wong is a Marvel Comics character best known as Doctor Strange’s loyal friend, valet, and powerful mystical ally.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wong Target entity description: Wong is a Marvel Comics character best known as Doctor Strange’s loyal friend, valet, and powerful mystical ally.
-
A.
Wong
Wong is a common Chinese surname shared by many people of Chinese descent worldwide.
-
B.
Mr. Wong
Mr. Wong is the enigmatic criminal mastermind and primary antagonist in the 1934 mystery film "The Mysterious Mr. Wong."
-
C.
Marcus Wong
Marcus Wong is a Canadian municipal politician who serves as the mayor of West Vancouver, British Columbia.
-
D.
Wong Tai Sin
Wong Tai Sin is a residential and cultural district in northern Kowloon, Hong Kong, best known for its famous Wong Tai Sin Temple and dense public housing estates.
-
E.
Sean Wong
Sean Wong is an American writer and editor known for his contributions to Asian American literature and for co-founding the Before Columbus Foundation, which promotes multicultural literature.
- 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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca84c209c8190b082a9b8499bedf7 |
completed | April 1, 2026, 5:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0305eb6e081908edba0ddab25e209 |
completed | April 3, 2026, 9:25 p.m. |
| NEDg | Description generation | batch_69d032eb2e708190b2d265ad7b49d084 |
completed | April 3, 2026, 9:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0337057048190af062152688599a1 |
completed | April 3, 2026, 9:38 p.m. |
Created at: March 30, 2026, 7:16 p.m.