Triple
T3793711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgian franc (Latin Monetary Union) |
E89717
|
entity |
| Predicate | standardizedFeatures |
P8032
|
FINISHED |
| Object | weight |
—
|
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: weight | Statement: [Belgian franc (Latin Monetary Union), standardizedFeatures, weight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardizedFeatures Context triple: [Belgian franc (Latin Monetary Union), standardizedFeatures, weight]
-
A.
standardizedFor
chosen
Indicates that something has been adjusted or converted to conform to a common standard, format, or reference so it can be consistently compared or used.
-
B.
standardizedBy
Indicates that one entity defines, regulates, or formalizes the standards or specifications by which another entity is created, measured, or operated.
-
C.
standardizedIn
Indicates that something has been formally defined, regulated, or made uniform within a particular standard, framework, or jurisdiction.
-
D.
firstStandardized
Indicates that an entity is the earliest or primary instance to which a standard or uniform specification has been first applied among comparable entities.
-
E.
standardizedSince
Indicates that something has been formally standardized starting from a specific point in time.
- 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_69aed9597d6881909b6ee3b9de859223 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecefa3608190a7a20ed6df6a64b2 |
completed | March 9, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69aee743c8d08190a9f9c97b836bd703 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:15 p.m.