Triple
T17908304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheese |
E447756
|
entity |
| Predicate | alignmentWithMac |
P129257
|
FINISHED |
| Object | antagonistic nuisance |
—
|
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: antagonistic nuisance | Statement: [Cheese, alignmentWithMac, antagonistic nuisance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alignmentWithMac Context triple: [Cheese, alignmentWithMac, antagonistic nuisance]
-
A.
alignsWith
Indicates that one entity is in agreement, harmony, or consistent correspondence with another in terms of position, direction, standard, or principle.
-
B.
alignmentMethod
Indicates the technique or procedure used to align one entity with another or with a reference standard.
-
C.
alignmentConcept
Indicates a conceptual or abstract relationship of alignment or correspondence between entities, such as agreement, compatibility, or shared orientation in some dimension.
-
D.
alignmentComponents
Indicates that one entity is composed of or associated with specific subparts or elements that together form its overall alignment.
-
E.
alignmentShape
Indicates that one entity’s shape is arranged, oriented, or matched in position relative to another entity’s shape.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49e9e4c9881908bfc3a83809d6b85 |
completed | April 19, 2026, 9:21 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
| PDg | Predicate description generation | batch_69e3db77df0c819084548168c62b398c |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:19 a.m.