Triple
T12229799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tai Kwun |
E291443
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object |
F Hall
F Hall is one of the restored historic buildings within Hong Kong’s Tai Kwun heritage and arts complex, repurposed for contemporary cultural and community uses.
|
E969220
|
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: F Hall | Statement: [Tai Kwun, hasComponent, F Hall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: F Hall Context triple: [Tai Kwun, hasComponent, F Hall]
-
A.
Farris
Farris is a surname most notably associated with Christine King Farris, an American educator, author, and the elder sister of Martin Luther King Jr.
-
B.
Furthman
Furthman is a surname most notably associated with American screenwriter Jules Furthman, known for his work on classic Hollywood films.
-
C.
F. Dick
F. Dick is a renowned German manufacturer of professional knives and sharpening tools, particularly known for its high-quality products made in Solingen.
-
D.
Fagan
Fagan is the family name of legendary American jazz singer Billie Holiday, born Eleanora Fagan.
-
E.
Farrell
Farrell is a surname of Irish origin borne by numerous notable individuals across fields such as entertainment, sports, and politics.
- 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: F Hall Triple: [Tai Kwun, hasComponent, F Hall]
Generated description
F Hall is one of the restored historic buildings within Hong Kong’s Tai Kwun heritage and arts complex, repurposed for contemporary cultural and community uses.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: F Hall Target entity description: F Hall is one of the restored historic buildings within Hong Kong’s Tai Kwun heritage and arts complex, repurposed for contemporary cultural and community uses.
-
A.
Farris
Farris is a surname most notably associated with Christine King Farris, an American educator, author, and the elder sister of Martin Luther King Jr.
-
B.
Furthman
Furthman is a surname most notably associated with American screenwriter Jules Furthman, known for his work on classic Hollywood films.
-
C.
F. Dick
F. Dick is a renowned German manufacturer of professional knives and sharpening tools, particularly known for its high-quality products made in Solingen.
-
D.
Fagan
Fagan is the family name of legendary American jazz singer Billie Holiday, born Eleanora Fagan.
-
E.
Farrell
Farrell is a surname of Irish origin borne by numerous notable individuals across fields such as entertainment, sports, and politics.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91ca34fe88190900c8791c70948b7 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60aad2d488190ba36588e3376ca1a |
completed | May 2, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69f60bdca250819090b4b4cc84d343f4 |
completed | May 2, 2026, 2:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60cd1668881908f43d895fcfba0aa |
completed | May 2, 2026, 2:40 p.m. |
Created at: April 8, 2026, 9:51 p.m.