Triple
T15030892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | stress–energy tensor |
E378339
|
entity |
| Predicate | T_{i0}Represents |
P116452
|
FINISHED |
| Object | momentum density |
—
|
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: momentum density | Statement: [stress–energy tensor, T_{i0}Represents, momentum density]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: T_{i0}Represents
Context triple: [stress–energy tensor, T_{i0}Represents, momentum density]
-
A.
topLevelRepresents
Indicates that one entity serves as the primary or overarching representation of another entity or concept at the highest level of abstraction or organization.
-
B.
isRepresentiveOf
Indicates that one entity serves as an official agent, spokesperson, or proxy acting on behalf of another entity.
-
C.
representationIn
Indicates that one entity serves as a depiction, model, or stand-in for another entity within a given context or medium.
-
D.
firstPartRepresents
Indicates that the initial segment or portion of something stands for, symbolizes, or denotes a larger whole or specific concept.
-
E.
rimRepresents
Indicates that one entity serves as a representation, model, or stand-in for another entity within a specific context or system.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e2416081908dfba48d7f7b4a84 |
completed | April 15, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:59 a.m.