Triple
T11014504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuala Lumpur Tower |
E260328
|
entity |
| Predicate | hasNumberOfStairs |
P1275
|
FINISHED |
| Object | about 2,058 steps |
—
|
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: about 2,058 steps | Statement: [Kuala Lumpur Tower, hasNumberOfStairs, about 2,058 steps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfStairs Context triple: [Kuala Lumpur Tower, hasNumberOfStairs, about 2,058 steps]
-
A.
hasStairway
Indicates that one entity includes or is connected to another entity by a stairway providing vertical access between levels.
-
B.
numberOfStairs
chosen
Indicates the quantity of stairs associated with or present in a given context or structure.
-
C.
hasStairsFacing
Indicates that one set of stairs is oriented toward or directly faces another object or direction.
-
D.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
E.
hasEscalators
Indicates that one entity is equipped with or contains escalators that can be used for movement between different levels or areas.
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797a49f648190a5144625d09dec6f |
completed | April 9, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69d72e96be6c8190a46c69f61b2d8cd4 |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:25 p.m.