Triple
T5798118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Provincial admiralties |
E128556
|
entity |
| Predicate | hasNumberOfUnits |
P19248
|
FINISHED |
| Object | five admiralties |
—
|
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: five admiralties | Statement: [Provincial admiralties, hasNumberOfUnits, five admiralties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfUnits Context triple: [Provincial admiralties, hasNumberOfUnits, five admiralties]
-
A.
numberOfUnits
chosen
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
B.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
C.
usesQuantity
Indicates that one entity employs or applies a specified amount or measure of another entity in performing an action or fulfilling a function.
-
D.
hasUnitNumber
Indicates that an entity is associated with a specific unit identifier or number within a larger building, complex, or organizational structure.
-
E.
hasRetailUnits
Indicates that one entity possesses, operates, or is associated with one or more retail units (such as stores or outlets).
- 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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b1304588190b59a18fb7b70a60f |
completed | March 22, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69c021d477008190946113f9859eeb90 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:51 p.m.