Triple
T37961134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shulker Shell |
E947010
|
entity |
| Predicate | typicalDropQuantity |
P5954
|
FINISHED |
| Object | 0–1 per Shulker |
—
|
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: 0–1 per Shulker | Statement: [Shulker Shell, typicalDropQuantity, 0–1 per Shulker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDropQuantity Context triple: [Shulker Shell, typicalDropQuantity, 0–1 per Shulker]
-
A.
typicalPackSize
Indicates the usual quantity of items contained together in a single package for that entity.
-
B.
hasNumberOfDrops
chosen
Indicates the quantity or count of drops associated with an entity or event.
-
C.
typicalBottleCount
Indicates the usual or standard number of bottles associated with something under normal conditions.
-
D.
typicalUnitSize
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
-
E.
mainQuantity
Indicates that the associated value represents the primary or principal quantity in a given context or relationship.
- 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_69f76ef7062c819091bfacb7e83aa1e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:20 p.m.