Triple
T9610602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leslie Chow |
E232088
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Mr. Chow |
E228236
|
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: Mr. Chow | Statement: [Leslie Chow, alsoKnownAs, Mr. Chow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Chow Context triple: [Leslie Chow, alsoKnownAs, Mr. Chow]
-
A.
Mr. Chow
chosen
Mr. Chow is a flamboyant, unpredictable, and often outrageous criminal associate who provides much of the chaotic comic relief in The Hangover film series.
-
B.
Mr. Wong
Mr. Wong is the enigmatic criminal mastermind and primary antagonist in the 1934 mystery film "The Mysterious Mr. Wong."
-
C.
Sam Poo Kong
Sam Poo Kong is a historic Chinese temple complex in Semarang, Indonesia, revered as a cultural and religious site linked to the legendary admiral Zheng He.
-
D.
Ka-chiu
Ka-chiu is the given name of John Lee Ka-chiu, the Chief Executive of Hong Kong and a former security official.
-
E.
Lady Zhang
Lady Zhang was the wife of Chinese warlord and military leader Wu Peifu, associated with the Beiyang government era in early 20th-century China.
- 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_69ca8485a90c819094fe40b42fde9d70 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a85d4c881909ccab2e972d97e68 |
completed | April 1, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d179513f9081909bcd9a456c640ba3 |
completed | April 4, 2026, 8:49 p.m. |
Created at: March 30, 2026, 8:08 p.m.