Triple
T20034283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CIPM Consultative Committee for Length |
E497216
|
entity |
| Predicate | focusesOnQuantity |
P79687
|
FINISHED |
| Object | length |
—
|
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: length | Statement: [CIPM Consultative Committee for Length, focusesOnQuantity, length]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnQuantity Context triple: [CIPM Consultative Committee for Length, focusesOnQuantity, length]
-
A.
concernsQuantity
chosen
Indicates that the relationship or statement specifically pertains to the amount, number, or measurable extent of something.
-
B.
usesQuantity
Indicates that one entity employs or applies a specified amount or measure of another entity in performing an action or fulfilling a function.
-
C.
mainQuantity
Indicates that the associated value represents the primary or principal quantity in a given context or relationship.
-
D.
relatesToQuantity
Indicates a relationship where one entity is associated with, depends on, or is characterized by a specific quantity or amount.
-
E.
stockKeepingUnitFocus
Indicates that the relationship or action is specifically concerned with, centered on, or targeted toward a particular stock keeping unit (SKU).
- 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662e6a7e481908069c1de2b3f94e0 |
completed | April 20, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:36 p.m.