Triple
T16105967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Better Luck Tomorrow |
E390738
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object |
Shirley Chan
Shirley Chan is a cinematographer best known for her work on the independent crime-drama film "Better Luck Tomorrow."
|
E1197543
|
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: Shirley Chan | Statement: [Better Luck Tomorrow, cinematographyBy, Shirley Chan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shirley Chan Context triple: [Better Luck Tomorrow, cinematographyBy, Shirley Chan]
-
A.
Vivian Chan
Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
-
B.
Anita Chan
Anita Chan is a prominent scholar known for her influential research on Chinese labor issues and labor rights.
-
C.
Yvonne Chan
Yvonne Chan is the maternal grandmother of August Chan Zuckerberg, the daughter of Facebook co-founder Mark Zuckerberg and pediatrician Priscilla Chan.
-
D.
Vivian Chow
Vivian Chow is a Hong Kong Cantopop singer and actress who rose to fame in the late 1980s and 1990s and became known as one of the era’s most popular idols.
-
E.
Teresa Cheng
Teresa Cheng is a film producer known for her work on major animated features, including entries in the Shrek franchise.
- 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: Shirley Chan Triple: [Better Luck Tomorrow, cinematographyBy, Shirley Chan]
Generated description
Shirley Chan is a cinematographer best known for her work on the independent crime-drama film "Better Luck Tomorrow."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shirley Chan Target entity description: Shirley Chan is a cinematographer best known for her work on the independent crime-drama film "Better Luck Tomorrow."
-
A.
Vivian Chan
Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
-
B.
Anita Chan
Anita Chan is a prominent scholar known for her influential research on Chinese labor issues and labor rights.
-
C.
Yvonne Chan
Yvonne Chan is the maternal grandmother of August Chan Zuckerberg, the daughter of Facebook co-founder Mark Zuckerberg and pediatrician Priscilla Chan.
-
D.
Vivian Chow
Vivian Chow is a Hong Kong Cantopop singer and actress who rose to fame in the late 1980s and 1990s and became known as one of the era’s most popular idols.
-
E.
Teresa Cheng
Teresa Cheng is a film producer known for her work on major animated features, including entries in the Shrek franchise.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6d81d081909e1315f4dbfd7369 |
completed | April 17, 2026, 9:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff79c74388190a10e0346426b0cbe |
completed | May 10, 2026, 3:12 a.m. |
| NEDg | Description generation | batch_69fff8de647481908e820b0e14bc7b76 |
completed | May 10, 2026, 3:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fff94cd32081908205ae383e58d148 |
completed | May 10, 2026, 3:19 a.m. |
Created at: April 10, 2026, 5 a.m.