Triple
T15661321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meat-shaped Stone |
E376571
|
entity |
| Predicate | museumInventoryType |
P119637
|
FINISHED |
| Object | jade object |
—
|
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: jade object | Statement: [Meat-shaped Stone, museumInventoryType, jade object]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: museumInventoryType Context triple: [Meat-shaped Stone, museumInventoryType, jade object]
-
A.
museumDisplayType
Indicates the manner or format in which items are presented or exhibited within a museum setting.
-
B.
hasMuseumType
Indicates that an entity is classified as a museum of a specific type or category.
-
C.
museumHolds
Indicates that a museum possesses, preserves, or has custody of a particular item or collection within its holdings.
-
D.
museumSection
Indicates that one entity is a section, area, or subdivision within a museum associated with the other entity.
-
E.
museumInventoryNumber
Indicates the unique catalog or inventory identifier assigned to an item within a museum’s collection.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef4e6a08190ad8bbafaa3612f22 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:15 a.m.