Triple
T7970855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanctum (Doctor Strange area) |
E185318
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Wong |
E96890
|
NE FINISHED |
How this triple was built (2 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: [Sanctum (Doctor Strange area), featuresCharacter, Wong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wong Context triple: [Sanctum (Doctor Strange area), featuresCharacter, Wong]
-
A.
Wong
chosen
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.
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.
-
D.
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.
-
E.
Kwan
Kwan is a Chinese-origin surname shared by many individuals, including the renowned American figure skater Michelle Kwan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca8297699481909b75a405f01e03af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bd304dc8190b9feee5e17fc66db |
completed | March 31, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe0b207ec8190a1a78e77a6bdb15e |
completed | March 31, 2026, 2:56 p.m. |
Created at: March 30, 2026, 5:13 p.m.