Triple
T19907327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zone System |
E478452
|
entity |
| Predicate | Zone 0 description |
P137776
|
FINISHED |
| Object | maximum black with no texture |
—
|
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: maximum black with no texture | Statement: [Zone System, Zone 0 description, maximum black with no texture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Zone 0 description Context triple: [Zone System, Zone 0 description, maximum black with no texture]
-
A.
startingZoneFor
Indicates the zone or area where an entity initially begins, is placed, or starts its activity or process.
-
B.
zonedUse
Indicates the designated or permitted type of land use assigned to a property or area under zoning regulations.
-
C.
zonedTo
Indicates that one entity is assigned or designated to fall within the jurisdiction, service area, or regulatory zone of another entity.
-
D.
numberOfZones
Indicates the quantity of distinct zones associated with or contained by a given entity.
-
E.
railwayZoneNumber
Indicates the specific numbered zone of a railway network within which the referenced entity is located or classified.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6598cc5108190bca2a47c9f8ef70f |
completed | April 20, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69e537ecda248190895c96afb6243823 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:52 p.m.