Triple
T17798303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronald Cheng |
E444350
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Vulgaria
Vulgaria is a 2012 Hong Kong black comedy film known for its raunchy humor and satirical take on the local film industry.
|
E1287638
|
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: Vulgaria | Statement: [Ronald Cheng, notableWork, Vulgaria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vulgaria Context triple: [Ronald Cheng, notableWork, Vulgaria]
-
A.
Bulgaria
Bulgaria is a Southeast European country on the Balkan Peninsula, known for its rich historical heritage, diverse landscapes, and role as a member of the European Union and NATO.
-
B.
Romania and Bulgaria
Romania and Bulgaria are neighboring countries in Southeastern Europe that share a historically contested border and are both members of the European Union and NATO.
-
C.
Romania
Romania is a southeastern European country known for its role in World War II, its Carpathian mountain landscapes, and its historical regions such as Transylvania.
-
D.
Rumen
Rumen is a masculine given name commonly used in Bulgaria and other Slavic countries.
-
E.
Bulga
Bulga is a rural locality in the Singleton Shire of New South Wales, Australia, known for its agricultural landscape and proximity to the Hunter Valley region.
- 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: Vulgaria Triple: [Ronald Cheng, notableWork, Vulgaria]
Generated description
Vulgaria is a 2012 Hong Kong black comedy film known for its raunchy humor and satirical take on the local film industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vulgaria Target entity description: Vulgaria is a 2012 Hong Kong black comedy film known for its raunchy humor and satirical take on the local film industry.
-
A.
Bulgaria
Bulgaria is a Southeast European country on the Balkan Peninsula, known for its rich historical heritage, diverse landscapes, and role as a member of the European Union and NATO.
-
B.
Romania and Bulgaria
Romania and Bulgaria are neighboring countries in Southeastern Europe that share a historically contested border and are both members of the European Union and NATO.
-
C.
Romania
Romania is a southeastern European country known for its role in World War II, its Carpathian mountain landscapes, and its historical regions such as Transylvania.
-
D.
Rumen
Rumen is a masculine given name commonly used in Bulgaria and other Slavic countries.
-
E.
Bulga
Bulga is a rural locality in the Singleton Shire of New South Wales, Australia, known for its agricultural landscape and proximity to the Hunter Valley region.
- 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e487fcfdc8819086f41152860dfe18 |
completed | April 19, 2026, 7:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02f84095f48190985b20bc8f049e5b |
completed | May 12, 2026, 9:52 a.m. |
| NEDg | Description generation | batch_6a02f9078e088190b2e84f219f7457ed |
completed | May 12, 2026, 9:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a02f98c91a481909739f2a8a681286d |
completed | May 12, 2026, 9:57 a.m. |
Created at: April 10, 2026, 10:13 a.m.