Triple
T21931374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brock Commons Tallwood House |
E541573
|
entity |
| Predicate | numberOfTimberStoreys |
P146602
|
FINISHED |
| Object | 17 |
—
|
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: 17 | Statement: [Brock Commons Tallwood House, numberOfTimberStoreys, 17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTimberStoreys Context triple: [Brock Commons Tallwood House, numberOfTimberStoreys, 17]
-
A.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
B.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
C.
storeysOfTallestTower
Indicates the number of storeys contained in the tallest tower associated with the given context or entity.
-
D.
hasBaseBuildingFloors
Indicates that something (such as a building or structure) has a specified number of floors in its base or main part.
-
E.
numberOfTrees
Indicates the count or quantity of trees associated with a given entity or context.
- F. None of above. chosen
Provenance (4 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_69e0c47d74488190a15119108794a307 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f123ff16148190843d92bbc1e9bb24 |
completed | April 28, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
| PDg | Predicate description generation | batch_69e6fb6991948190a428c3c3bfd1c3b8 |
completed | April 21, 2026, 4:22 a.m. |
Created at: April 16, 2026, 7:47 p.m.