Triple
T14876762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tales of Suspense #39 |
E349886
|
entity |
| Predicate | firstAppearanceOf |
P17193
|
FINISHED |
| Object | Wong-Chu |
E1126037
|
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-Chu | Statement: [Tales of Suspense #39, firstAppearanceOf, Wong-Chu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wong-Chu Context triple: [Tales of Suspense #39, firstAppearanceOf, Wong-Chu]
-
A.
Wong-Chu
chosen
Wong-Chu is a Marvel Comics supervillain best known as the warlord whose actions lead to Tony Stark becoming Iron Man.
-
B.
Wong
Wong is a common Chinese surname shared by many people of Chinese descent worldwide.
-
C.
Wong
Wong is a Marvel Comics character best known as Doctor Strange’s loyal friend, valet, and powerful mystical ally.
-
D.
Chow Chung
Chow Chung was a Hong Kong actor known for his supporting roles in numerous Cantonese films and television dramas from the mid-20th century.
-
E.
Kwai Chung
Kwai Chung is a major industrial and residential area in Hong Kong best known for its large container terminals and logistics facilities that form a core part of the city’s port operations.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e4e4448190a8796573bc6d1069 |
completed | April 15, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72ac9f6481908f7b4f63a11fe16c |
completed | May 8, 2026, 11:33 p.m. |
Created at: April 10, 2026, 1:55 a.m.