Triple
T1963970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctor Stephen Strange |
E42646
|
entity |
| Predicate | ally |
P4662
|
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: [Doctor Stephen Strange, ally, Wong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wong Context triple: [Doctor Stephen Strange, ally, Wong]
-
A.
Wong
chosen
Wong is a common Chinese surname shared by many people of Chinese descent worldwide.
-
B.
Kwan
Kwan is a Chinese-origin surname shared by many individuals, including the renowned American figure skater Michelle Kwan.
-
C.
Wing Lei
Wing Lei is an upscale Chinese fine-dining restaurant at Wynn Las Vegas, renowned for its elegant décor and refined Cantonese cuisine.
-
D.
Jason Wong
Jason Wong is a British actor known for his roles in film and television, including his appearance in Guy Ritchie's crime-comedy series "The Gentlemen."
-
E.
Hung Sin Nui
Hung Sin Nui was a renowned Cantonese opera diva and film actress, celebrated as one of the most iconic performers in the history of Cantonese opera.
- 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_69a88711151c8190940b2572095059d7 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3ada4148190ad830d4a3d7fd662 |
completed | March 7, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfbd32eb88190a2069b6490b12e5d |
completed | March 8, 2026, 10:44 p.m. |
Created at: March 4, 2026, 7:36 p.m.