Triple
T15711903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Only God Forgives |
E380858
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Chang
Chang is a mysterious, sword-wielding police lieutenant in the neo-noir film "Only God Forgives," known for his brutal, almost supernatural sense of justice.
|
E1172449
|
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: Chang | Statement: [Only God Forgives, mainCharacter, Chang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chang Context triple: [Only God Forgives, mainCharacter, Chang]
-
A.
Chang
Chang is a 1927 silent documentary-style adventure film set in the jungles of Siam, co-directed by Merian C. Cooper and Ernest B. Schoedsack, known for its depiction of human–nature conflict and elephant stampedes.
-
B.
Chang
Chang is a common Chinese surname shared by many individuals across the Chinese-speaking world.
-
C.
Youchang
Youchang is the courtesy name of Ma Su, a Shu Han military general who served under Zhuge Liang during China’s Three Kingdoms period.
-
D.
Chun
Chun is the given name of Peng Chun Chang, a prominent Chinese philosopher and diplomat who helped draft the Universal Declaration of Human Rights.
-
E.
Chon
Chon is a former Navy SEAL and one of the two marijuana-growing protagonists in Oliver Stone’s crime thriller film "Savages."
- 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: Chang Triple: [Only God Forgives, mainCharacter, Chang]
Generated description
Chang is a mysterious, sword-wielding police lieutenant in the neo-noir film "Only God Forgives," known for his brutal, almost supernatural sense of justice.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chang Target entity description: Chang is a mysterious, sword-wielding police lieutenant in the neo-noir film "Only God Forgives," known for his brutal, almost supernatural sense of justice.
-
A.
Chang
Chang is a 1927 silent documentary-style adventure film set in the jungles of Siam, co-directed by Merian C. Cooper and Ernest B. Schoedsack, known for its depiction of human–nature conflict and elephant stampedes.
-
B.
Chang
Chang is a common Chinese surname shared by many individuals across the Chinese-speaking world.
-
C.
Youchang
Youchang is the courtesy name of Ma Su, a Shu Han military general who served under Zhuge Liang during China’s Three Kingdoms period.
-
D.
Chun
Chun is the given name of Peng Chun Chang, a prominent Chinese philosopher and diplomat who helped draft the Universal Declaration of Human Rights.
-
E.
Chon
Chon is a former Navy SEAL and one of the two marijuana-growing protagonists in Oliver Stone’s crime thriller film "Savages."
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f8f5d6081908243fa59b46b7c76 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff757f571881908015fe68df2a5e69 |
completed | May 9, 2026, 5:57 p.m. |
| NEDg | Description generation | batch_69ff769d305881908791ffcb0a30ee35 |
completed | May 9, 2026, 6:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff770b73d48190a422a0760c03f763 |
completed | May 9, 2026, 6:03 p.m. |
Created at: April 10, 2026, 4:45 a.m.