Triple
T378896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minkowski space-time |
E8632
|
entity |
| Predicate | metricTensorComponent |
P12676
|
FINISHED |
| Object | diag(-1,1,1,1) |
—
|
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: diag(-1,1,1,1) | Statement: [Minkowski space-time, metricTensorComponent, diag(-1,1,1,1)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metricTensorComponent Context triple: [Minkowski space-time, metricTensorComponent, diag(-1,1,1,1)]
-
A.
tensorRank
Indicates the rank (number of indices or dimensions) associated with a given tensor.
-
B.
meter
Indicates a measurement relationship where one entity quantifies the length, distance, or extent of another in meters.
-
C.
dimension
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
-
D.
dimensionType
Indicates the specific kind or category of dimension that characterizes how something is measured or structured.
-
E.
typicalRank
Indicates the usual or most common rank or position an entity holds within a given ordering or hierarchy.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec2974988190a1d6316cbb5159c8 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e964d4b481909290e474b0341e3c |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2eae0bd7081908197bbf5c55fe647 |
completed | Feb. 28, 2026, 1:17 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.