Triple
T16553864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lafayette Towers Apartments East |
E402140
|
entity |
| Predicate | isResidentialDensity |
P70081
|
FINISHED |
| Object | high-rise |
—
|
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: high-rise | Statement: [Lafayette Towers Apartments East, isResidentialDensity, high-rise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isResidentialDensity Context triple: [Lafayette Towers Apartments East, isResidentialDensity, high-rise]
-
A.
hasHousingDensity
chosen
Indicates the relationship between an area and the concentration of housing units within that area, typically measured as units per unit of land.
-
B.
hasPopulationDensityType
Indicates the classification of an area based on how densely populated it is (e.g., urban, suburban, rural).
-
C.
hasPopulationDensity
Indicates the number of individuals (e.g., people, organisms) per unit area associated with a given entity or region.
-
D.
isResidential
Indicates that something is used or designated primarily for people to live in, rather than for commercial, industrial, or other non-living purposes.
-
E.
isDenselyPopulated
Indicates that a place has a high concentration of inhabitants relative to its area.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34fc737ac8190b755e2a39b6ef32b |
completed | April 18, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_69e296a47b7481909d9958158510c806 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:15 a.m.