Triple
T13400710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Machine |
E319818
|
entity |
| Predicate | nicknameConnotation |
P39779
|
FINISHED |
| Object | relentless efficiency |
—
|
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: relentless efficiency | Statement: [Red Machine, nicknameConnotation, relentless efficiency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nicknameConnotation Context triple: [Red Machine, nicknameConnotation, relentless efficiency]
-
A.
nickNameMeaning
Indicates that a nickname is associated with a particular meaning, interpretation, or significance.
-
B.
nicknameEmphasizes
chosen
Indicates that a nickname highlights or draws special attention to a particular characteristic, trait, or aspect of the entity it refers to.
-
C.
nicknameCategory
Indicates that one entity is a nickname and the other entity is the category or type that this nickname belongs to.
-
D.
nameLiterallyMeans
Indicates that the literal meaning or direct translation of one entity’s name is given by the other entity.
-
E.
nicknameForRole
Indicates that one entity is an informal or alternative name commonly used to refer to a particular role or position represented by another entity.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae47e99081909d8b5dba97a11988 |
completed | April 12, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:34 p.m.