Triple
T7968629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law Kar-ying |
E185267
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Law Ka-ying |
E185267
|
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: Law Ka-ying | Statement: [Law Kar-ying, alsoKnownAs, Law Ka-ying]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Law Ka-ying Context triple: [Law Kar-ying, alsoKnownAs, Law Ka-ying]
-
A.
Law Kar-ying
chosen
Law Kar-ying is a renowned Hong Kong Cantonese opera performer and actor known for his versatile stage and screen roles.
-
B.
Kar-ying
Kar-ying is the given name of Law Kar-ying, a veteran Hong Kong actor and Cantonese opera performer known for his roles in film and television.
-
C.
K. Yin
K. Yin is a technical contributor known for coauthoring IETF RFC 6145 on IP/ICMP translation between IPv4 and IPv6 networks.
-
D.
Ken Kao
Ken Kao is an American film producer known for backing a range of independent and auteur-driven projects.
-
E.
Hau Lee
Hau Lee is a prominent operations and supply chain management scholar known for his influential research on global supply networks and his long-standing professorship at Stanford Graduate School of Business.
- 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_69cb3bd06ee081908c5080003fb7b8f7 |
completed | March 31, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc566afad88190b53f228d836619de |
completed | March 31, 2026, 11:19 p.m. |
Created at: March 30, 2026, 5:13 p.m.