Triple
T21446308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | acid-green Quick-Quotes Quill |
E529084
|
entity |
| Predicate | effectOnOutput |
P144379
|
FINISHED |
| Object | makes quotes more dramatic |
—
|
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: makes quotes more dramatic | Statement: [acid-green Quick-Quotes Quill, effectOnOutput, makes quotes more dramatic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnOutput Context triple: [acid-green Quick-Quotes Quill, effectOnOutput, makes quotes more dramatic]
-
A.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
B.
effectOnSystem
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
C.
effectOnSupply
Indicates how one factor or action changes the availability or quantity of a given supply.
-
D.
effectOnOthers
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
E.
effectOnMachines
Indicates the influence or impact that one entity, condition, or action has on machines and their behavior or performance.
- F. None of above. chosen
Provenance (4 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9cea7bc81909ee3e1cdeda1fe7e |
completed | April 23, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69e631df1b38819088d3604854e697b4 |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e63d2aca38819094d312078feaa436 |
completed | April 20, 2026, 2:50 p.m. |
Created at: April 16, 2026, 6:06 p.m.