Triple
T461760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Einstein tensor |
E7353
|
entity |
| Predicate | hasDivergence |
P14246
|
FINISHED |
| Object | zero |
—
|
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: zero | Statement: [Einstein tensor, hasDivergence, zero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDivergence Context triple: [Einstein tensor, hasDivergence, zero]
-
A.
hasCurvatureDivergence
Indicates that one entity exhibits a difference or variation in curvature relative to another entity or reference.
-
B.
hasDelta
Indicates that there is a change, difference, or deviation between two related states, values, or versions of something.
-
C.
hasDerivative
Indicates that one entity is derived, obtained, or produced from another through some transformation, process, or modification.
-
D.
hasHistoricalShiftFrom
Indicates a relationship where one state, practice, or condition has been replaced or transformed over time from another earlier state, practice, or condition.
-
E.
hasHistoricalShiftTo
Indicates a change over time in which one state, condition, or configuration is replaced or transformed into another in a historically traceable way.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efbed5b88190a45716812eb4cfdf |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2ede8eac081908dffade6a5e7950b |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ef06d2fc8190b379d575215a8518 |
completed | Feb. 28, 2026, 1:35 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.