Triple
T29312062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Chancery Center |
E743260
|
entity |
| Predicate | zoningOrUseType |
P116763
|
FINISHED |
| Object | chancery use |
—
|
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: chancery use | Statement: [International Chancery Center, zoningOrUseType, chancery use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zoningOrUseType Context triple: [International Chancery Center, zoningOrUseType, chancery use]
-
A.
zonedUse
chosen
Indicates the designated or permitted type of land use assigned to a property or area under zoning regulations.
-
B.
zoningAuthority
Indicates that an entity has official power or jurisdiction to regulate land use and development within a specified area.
-
C.
hasZoningRestriction
Indicates that an entity is subject to a specific zoning-related limitation or regulatory constraint.
-
D.
hasIndustrialZoning
Indicates that a given area or property is designated for industrial use under zoning regulations.
-
E.
servesLandUseType
Indicates that one entity functions to support, accommodate, or provide services for a specified land use type.
- 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_69f0912502c8819087d9e8398ee991a8 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f665e5ade481908eac1b24726ba5b5 |
completed | May 2, 2026, 9 p.m. |
| PD | Predicate disambiguation | batch_69f660f2e3708190ab658652bcfc04d0 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 1:17 p.m.