Triple
T8633133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keangnam Landmark 72 complex |
E204452
|
entity |
| Predicate | floorCountOfResidentialTowers |
P56315
|
FINISHED |
| Object | 48 |
—
|
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: 48 | Statement: [Keangnam Landmark 72 complex, floorCountOfResidentialTowers, 48]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floorCountOfResidentialTowers Context triple: [Keangnam Landmark 72 complex, floorCountOfResidentialTowers, 48]
-
A.
numberOfResidentialFloors
chosen
Indicates the total count of floors in a building that are designated for residential use.
-
B.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
C.
floorCountOfSurroundingBuildings
Indicates the number of floors in the buildings that are located around or near a given reference building or area.
-
D.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
E.
storeysOfTallestTower
Indicates the number of storeys contained in the tallest tower associated with the given context or 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc47944d1c819081f448f14d04bf9d |
completed | March 31, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69cc455d6d448190a2da2a319ac78c37 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:27 p.m.