Triple
T22535749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcy Houses |
E557147
|
entity |
| Predicate | numberOfStoriesPerBuilding |
P1728
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Marcy Houses, numberOfStoriesPerBuilding, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStoriesPerBuilding Context triple: [Marcy Houses, numberOfStoriesPerBuilding, 6]
-
A.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
B.
numberOfFloors
chosen
Indicates the total count of distinct floor 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.
storeysOfTallestTower
Indicates the number of storeys contained in the tallest tower associated with the given context or entity.
-
E.
numberOfResidentialFloors
Indicates the total count of floors in a building that are designated for residential use.
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15edad0248190b990ddffbc786e05 |
completed | April 29, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69e898c864148190a3f5feec7967d49c |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:51 p.m.