Triple
T27267556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tai Koo Shing |
E687947
|
entity |
| Predicate | numberOfResidentialBlocks |
P92310
|
FINISHED |
| Object | over 60 |
—
|
LITERAL FINISHED |
How this triple was built (2 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: over 60 | Statement: [Tai Koo Shing, numberOfResidentialBlocks, over 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfResidentialBlocks Context triple: [Tai Koo Shing, numberOfResidentialBlocks, over 60]
-
A.
numberOfResidentialFloors
Indicates the total count of floors in a building that are designated for residential use.
-
B.
hasResidentialFloors
Indicates that an entity (such as a building or structure) includes one or more floors designated for residential use.
-
C.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
D.
numberOfHousingUnits
Indicates the total count of distinct housing units associated with an entity or within a specified area.
-
E.
numberOfBlocks
chosen
Indicates the quantity of discrete block units associated with or contained by a given entity.
- F. None of above.
Provenance (3 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_69ef3557abc481908bf3c146f0f3356a |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69feb342994081909481ec8ec5d44928 |
completed | May 9, 2026, 4:08 a.m. |
| PD | Predicate disambiguation | batch_69feb046e4e48190b96649aa28529cc9 |
completed | May 9, 2026, 3:55 a.m. |
Created at: April 27, 2026, 10:57 a.m.