Triple
T19503071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pan Peninsula West Tower |
E487950
|
entity |
| Predicate | hasNumberOfResidentialUnits |
P19276
|
FINISHED |
| Object | more than 400 apartments |
—
|
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: more than 400 apartments | Statement: [Pan Peninsula West Tower, hasNumberOfResidentialUnits, more than 400 apartments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfResidentialUnits Context triple: [Pan Peninsula West Tower, hasNumberOfResidentialUnits, more than 400 apartments]
-
A.
hasResidentialFloors
Indicates that an entity (such as a building or structure) includes one or more floors designated for residential use.
-
B.
numberOfHousingUnits
chosen
Indicates the total count of distinct housing units associated with an entity or within a specified area.
-
C.
numberOfResidentialFloors
Indicates the total count of floors in a building that are designated for residential use.
-
D.
isResidentialUnitOf
Indicates that a specific residential unit (e.g., apartment, house) belongs to or is part of a larger property, building, or complex.
-
E.
hasHousingUnits
Indicates that an entity possesses or contains a specified number or set of housing units.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6350f8d888190a4809c83522933d4 |
completed | April 20, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:40 p.m.