Triple
T6177785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shaanxi History Museum |
E137861
|
entity |
| Predicate | buildingArea |
P175
|
FINISHED |
| Object | over 50000 square meters |
—
|
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: over 50000 square meters | Statement: [Shaanxi History Museum, buildingArea, over 50000 square meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingArea Context triple: [Shaanxi History Museum, buildingArea, over 50000 square meters]
-
A.
roofArea
Indicates the total surface area covered by the roof of a structure.
-
B.
hasFloorArea
Indicates that an entity possesses a specified amount of floor space as a measurable area.
-
C.
grossLeasableArea
Indicates the total floor area within a property that is available to be leased to tenants, excluding common or non-leasable spaces.
-
D.
area
chosen
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
E.
architectureProperty
Indicates that a specified architectural characteristic or feature is attributed to, or associated with, an entity.
- 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_69c008a80f748190ba3d07ffc81acb29 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05dc9f3d88190ab46b3b246f5a8df |
completed | March 22, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69c055fa0a808190bda37832e3ac150c |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:18 p.m.