Triple
T38147744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UNIVAC II |
E952664
|
entity |
| Predicate | tapeDensity |
P190141
|
FINISHED |
| Object | 128 bits per inch |
—
|
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: 128 bits per inch | Statement: [UNIVAC II, tapeDensity, 128 bits per inch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tapeDensity Context triple: [UNIVAC II, tapeDensity, 128 bits per inch]
-
A.
carpetKnotDensity
Indicates the number of knots per unit area in a carpet, reflecting how densely the carpet is knotted.
-
B.
typeOfDensity
Indicates the specific category or kind of density (e.g., mass, population, charge) that characterizes a given quantity or measurement.
-
C.
thickness
Indicates the measure of how deep or wide an object or layer is from one surface or side to its opposite.
-
D.
furDensity
Indicates the thickness or concentration of fur covering an entity’s body or a specific body part.
-
E.
hasMeanDensity
Indicates that one entity possesses a specified average mass per unit volume (mean density).
- 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_69f76f0a67f4819080c492f61d688fcc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcb089a8f881909aa9e722babd43f7 |
completed | May 7, 2026, 3:32 p.m. |
| PD | Predicate disambiguation | batch_69fc45666c5c8190913bd632ac0e5b84 |
completed | May 7, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69fcb088aac481909db90804faff315f |
completed | May 7, 2026, 3:32 p.m. |
Created at: May 3, 2026, 4:21 p.m.