Triple
T22737608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrhenius plot |
E562315
|
entity |
| Predicate | interceptRepresents |
P149537
|
FINISHED |
| Object | ln(A) |
—
|
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: ln(A) | Statement: [Arrhenius plot, interceptRepresents, ln(A)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interceptRepresents Context triple: [Arrhenius plot, interceptRepresents, ln(A)]
-
A.
interceptedBy
Indicates that an action, communication, or movement is stopped, captured, or diverted by another agent before reaching its intended target or destination.
-
B.
designedToIntercept
Indicates that one entity is purposefully created or configured to detect, block, or otherwise interrupt the actions, movement, or effects of another entity.
-
C.
cornerRepresents
Indicates that a particular corner in a structure, diagram, or space stands for or symbolizes another element, concept, or feature.
-
D.
locationOfInterception
Indicates the place where an interception event occurs between entities.
-
E.
interceptingPlayer
Indicates that one player takes possession of or disrupts a pass, throw, or transmission intended for another player or target.
- 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_69e24550859c81908727d91efc3a81b4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179707fd081909aed9b2f62b9f842 |
completed | April 29, 2026, 3:22 a.m. |
| PD | Predicate disambiguation | batch_69eed2a971c0819088af574e40c9343f |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb5681f88190821129ced752f190 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:22 p.m.