Triple
T31462271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kangbashi District |
E802631
|
entity |
| Predicate | initialOccupancy |
P180814
|
FINISHED |
| Object | low |
—
|
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: low | Statement: [Kangbashi District, initialOccupancy, low]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: initialOccupancy Context triple: [Kangbashi District, initialOccupancy, low]
-
A.
firstOccupied
Indicates that an entity was the initial or earliest occupant of a particular place, position, or resource.
-
B.
occupancyRequirement
Indicates that a condition specifies how many or which entities must be present in or using a particular space or resource.
-
C.
peakOccupation
Indicates the time or context in which an entity reaches its highest level of activity, usage, or occupancy.
-
D.
approximateOccupation
Indicates that one entity is inferred or estimated to be the occupation or job role of another entity, rather than being known with certainty.
-
E.
initialAvailability
Indicates the starting level or state of availability of an entity before any changes or updates occur.
- 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_69f348c84c1c81908739f100ecf7394e |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
| PDg | Predicate description generation | batch_69f7516c538481908c6e55cf76add098 |
completed | May 3, 2026, 1:45 p.m. |
Created at: April 30, 2026, 9:20 p.m.