Triple
T2022267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Watchmen (film) |
E44131
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Alex Tse
Alex Tse is an American screenwriter and producer best known for co-writing the film adaptation of the graphic novel "Watchmen."
|
E227854
|
NE FINISHED |
How this triple was built (4 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: Alex Tse | Statement: [Watchmen (film), screenwriter, Alex Tse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alex Tse Context triple: [Watchmen (film), screenwriter, Alex Tse]
-
A.
Gerald Chan
Gerald Chan is a Hong Kong-born American billionaire investor and philanthropist known for major donations to Harvard University and leadership of the Morningside Group.
-
B.
Norman Chan
Norman Chan is a Hong Kong banker and civil servant best known for serving as Chief Executive of the Hong Kong Monetary Authority.
-
C.
Savio Kwan
Savio Kwan is a business executive best known for his leadership roles at Alibaba Group, where he helped guide the company’s early growth and international expansion.
-
D.
Tony Wu
Tony Wu is a member of the technical team at xAI, the artificial intelligence company founded by Elon Musk.
-
E.
Michael Chan
Michael Chan is a common personal name shared by multiple individuals across fields such as politics, business, and entertainment.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Alex Tse Triple: [Watchmen (film), screenwriter, Alex Tse]
Generated description
Alex Tse is an American screenwriter and producer best known for co-writing the film adaptation of the graphic novel "Watchmen."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alex Tse Target entity description: Alex Tse is an American screenwriter and producer best known for co-writing the film adaptation of the graphic novel "Watchmen."
-
A.
Gerald Chan
Gerald Chan is a Hong Kong-born American billionaire investor and philanthropist known for major donations to Harvard University and leadership of the Morningside Group.
-
B.
Norman Chan
Norman Chan is a Hong Kong banker and civil servant best known for serving as Chief Executive of the Hong Kong Monetary Authority.
-
C.
Savio Kwan
Savio Kwan is a business executive best known for his leadership roles at Alibaba Group, where he helped guide the company’s early growth and international expansion.
-
D.
Tony Wu
Tony Wu is a member of the technical team at xAI, the artificial intelligence company founded by Elon Musk.
-
E.
Michael Chan
Michael Chan is a common personal name shared by multiple individuals across fields such as politics, business, and entertainment.
- F. None of above. chosen
Provenance (5 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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8efbe148190901d3650aa60408a |
completed | March 7, 2026, 5:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1fe88e8881909f2e64ebe23b6d1f |
completed | March 9, 2026, 1:18 a.m. |
| NEDg | Description generation | batch_69ae20641b088190bdbc7c39736eb585 |
completed | March 9, 2026, 1:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae20e214a88190b85432b9e47cde12 |
completed | March 9, 2026, 1:22 a.m. |
Created at: March 4, 2026, 7:38 p.m.