Triple
T38114478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J’adore Absolu |
E951752
|
entity |
| Predicate | intensityComparedToOriginal |
P196856
|
FINISHED |
| Object | richer |
—
|
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: richer | Statement: [J’adore Absolu, intensityComparedToOriginal, richer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intensityComparedToOriginal Context triple: [J’adore Absolu, intensityComparedToOriginal, richer]
-
A.
productionComparedToOriginal
Indicates a relationship where a production is evaluated or measured in comparison to an original version.
-
B.
intensityScale
Indicates the degree or level of strength, magnitude, or severity associated with an event, property, or measurement, typically according to a defined scale.
-
C.
violenceLevelComparedToOriginal
Indicates the degree to which the level of violence in one version differs from that in the original version.
-
D.
hasGreaterNoiseReductionThan
Indicates that one entity provides a higher level of noise reduction compared to another entity.
-
E.
originalIllumination
Indicates that an entity provides the initial or primary source of light or illumination for another entity or context.
- 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_69f76f07734c8190814e937e12257a78 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fe6b7c785c8190aaab06019f571434 |
completed | May 8, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fe68edef20819081c77f9607b944dd |
completed | May 8, 2026, 10:51 p.m. |
| PDg | Predicate description generation | batch_69fe6b7a823881909dc2037fe25bea24 |
completed | May 8, 2026, 11:02 p.m. |
Created at: May 3, 2026, 4:21 p.m.