Triple
T14911074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tukey's fences |
E371260
|
entity |
| Predicate | commonlyUsesMultiplier |
P1459
|
FINISHED |
| Object | 1.5 for regular outliers |
—
|
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: 1.5 for regular outliers | Statement: [Tukey's fences, commonlyUsesMultiplier, 1.5 for regular outliers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyUsesMultiplier Context triple: [Tukey's fences, commonlyUsesMultiplier, 1.5 for regular outliers]
-
A.
multiplicative
Indicates a relationship where one quantity is obtained by multiplying another quantity (or quantities), often expressing scaling, proportionality, or product-based interaction between them.
-
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.
usesFrequency
Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
-
D.
multipleUnit
Indicates that an entity is composed of or associated with more than one unit of the same type.
-
E.
usesMetric
chosen
Indicates that one entity adopts, applies, or relies on a particular metric or measurement standard in its operation, evaluation, or description.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded61c6b9c8190a92934d49b98fe46 |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a4a14a88190951bb8f4c60bd37b |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:26 a.m.