Triple
T20977154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mach-IV scale |
E516654
|
entity |
| Predicate | hasScoring |
P15617
|
FINISHED |
| Object | total Machiavellianism score |
—
|
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: total Machiavellianism score | Statement: [Mach-IV scale, hasScoring, total Machiavellianism score]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScoring Context triple: [Mach-IV scale, hasScoring, total Machiavellianism score]
-
A.
hasScoreRecord
Indicates that an entity is associated with a specific score entry or scoring record.
-
B.
isScoreFor
chosen
Indicates that one value represents the score or result associated with a particular entity, event, or performance.
-
C.
hasScoreSystem
Indicates that an entity uses, is governed by, or is associated with a particular scoring or rating system.
-
D.
hasScoreType
Indicates that an entity is associated with a particular type or category of score.
-
E.
hasScoreCharacteristic
Indicates that one entity possesses or is associated with a particular scoring-related characteristic or property.
- 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_69e0b4fee5ac8190875fa9ceba1a5e5e |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fba4a0dc819083b90795d26adfff |
completed | April 21, 2026, 4:23 a.m. |
| PD | Predicate disambiguation | batch_69e5dbe6976081908abd4e9c8734bae9 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 1:47 p.m.