Triple
T17075092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diocesan Boys’ School |
E414326
|
entity |
| Predicate | hasAlumnus |
P51
|
FINISHED |
| Object |
Joshua Wong
Joshua Wong is a prominent Hong Kong pro-democracy activist and politician known for his leadership role in the 2014 Umbrella Movement and subsequent advocacy for civil liberties.
|
E1249335
|
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: Joshua Wong | Statement: [Diocesan Boys’ School, hasAlumnus, Joshua Wong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joshua Wong Context triple: [Diocesan Boys’ School, hasAlumnus, Joshua Wong]
-
A.
Chan Yi-kan
Chan Yi-kan is the wife of acclaimed Hong Kong film director Wong Kar-wai.
-
B.
Michael Yu
Michael Yu is a prominent Chinese entrepreneur and educator best known as the founder of New Oriental Education & Technology Group, one of China’s largest private education providers.
-
C.
Michael Wong
Michael Wong is a Hong Kong-based actor and singer known for his roles in action and crime films across Asian cinema.
-
D.
Matthew Lai
Matthew Lai is a computer scientist and AI researcher known for his work on deep reinforcement learning systems such as AlphaGo Zero.
-
E.
Alex Tse
Alex Tse is an American screenwriter and producer best known for co-writing the film adaptation of the graphic novel "Watchmen."
- 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: Joshua Wong Triple: [Diocesan Boys’ School, hasAlumnus, Joshua Wong]
Generated description
Joshua Wong is a prominent Hong Kong pro-democracy activist and politician known for his leadership role in the 2014 Umbrella Movement and subsequent advocacy for civil liberties.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Joshua Wong Target entity description: Joshua Wong is a prominent Hong Kong pro-democracy activist and politician known for his leadership role in the 2014 Umbrella Movement and subsequent advocacy for civil liberties.
-
A.
Chan Yi-kan
Chan Yi-kan is the wife of acclaimed Hong Kong film director Wong Kar-wai.
-
B.
Michael Yu
Michael Yu is a prominent Chinese entrepreneur and educator best known as the founder of New Oriental Education & Technology Group, one of China’s largest private education providers.
-
C.
Michael Wong
Michael Wong is a Hong Kong-based actor and singer known for his roles in action and crime films across Asian cinema.
-
D.
Matthew Lai
Matthew Lai is a computer scientist and AI researcher known for his work on deep reinforcement learning systems such as AlphaGo Zero.
-
E.
Alex Tse
Alex Tse is an American screenwriter and producer best known for co-writing the film adaptation of the graphic novel "Watchmen."
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbc47808819088a4ca039689b213 |
completed | April 18, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012edfda588190aff6c6d4c8d64ddd |
completed | May 11, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_6a01317efec48190ae812586579b1039 |
completed | May 11, 2026, 1:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0131e5acb4819098ad7c4532c4118a |
completed | May 11, 2026, 1:33 a.m. |
Created at: April 10, 2026, 5:34 a.m.