Triple
T32316151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirchhoff stress tensor |
E825637
|
entity |
| Predicate | frameIndifference |
P173961
|
FINISHED |
| Object | objective stress measure |
—
|
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: objective stress measure | Statement: [Kirchhoff stress tensor, frameIndifference, objective stress measure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frameIndifference Context triple: [Kirchhoff stress tensor, frameIndifference, objective stress measure]
-
A.
frame
Indicates placing or presenting something within a particular context, structure, or perspective that shapes how it is interpreted.
-
B.
frameDependent
Indicates that the truth or interpretation of the relationship depends on the particular reference frame, context, or perspective from which it is evaluated.
-
C.
frameDuration
Indicates the length of time that a single frame in a sequence (such as video or animation) is displayed before advancing to the next frame.
-
D.
framesAs
Indicates how one entity presents, characterizes, or interprets another entity or situation in a particular light or context.
-
E.
framesViewOf
Indicates that one entity provides a framing, perspective, or interpretive context through which another entity is viewed or understood.
- 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_69f3491213b88190a57094d8697a7455 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bdbb00d4819083dd799d7d417f20 |
completed | May 3, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69f6b632cf788190a3d0c08cd026b84b |
completed | May 3, 2026, 2:42 a.m. |
| PDg | Predicate description generation | batch_69f6b960ca4081909a77690c2b122f5e |
completed | May 3, 2026, 2:56 a.m. |
Created at: May 1, 2026, 12:46 a.m.