Triple
T31776346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MLC (multi-level cell) |
E811073
|
entity |
| Predicate | hasLowerDensityThan |
P195402
|
FINISHED |
| Object | TLC (triple-level cell) |
—
|
NE NERFINISHED |
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: TLC (triple-level cell) | Statement: [MLC (multi-level cell), hasLowerDensityThan, TLC (triple-level cell)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLowerDensityThan Context triple: [MLC (multi-level cell), hasLowerDensityThan, TLC (triple-level cell)]
-
A.
hasLowDensity
Indicates that the subject possesses a density value that is below a defined or typical threshold.
-
B.
hasLowerConcentrationThan
Indicates that the concentration of one entity is lower than the concentration of another entity.
-
C.
hasLowerColumnDensityLimitThan
Indicates that the column density of one entity is constrained to be lower than the column density of another entity.
-
D.
hasLowerThroughputThan
Indicates that one entity’s throughput is less than that of another entity.
-
E.
hasLowerFrequencyIn
Indicates that one entity occurs or appears less frequently within a specified context than another entity.
- 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_69f348e544a48190ab6e700b05f6438c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fdd07a34c08190982b8c61c2775cf6 |
completed | May 8, 2026, noon |
| PD | Predicate disambiguation | batch_69fdbd25c7908190b72fca8de7ce503f |
completed | May 8, 2026, 10:38 a.m. |
| PDg | Predicate description generation | batch_69fdd07724f88190a33ec602642d2ea3 |
completed | May 8, 2026, noon |
Created at: April 30, 2026, 11:35 p.m.