Triple
T27556518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sawhorse projection |
E695649
|
entity |
| Predicate | helpsDistinguish |
P9157
|
FINISHED |
| Object | staggered vs eclipsed conformers |
—
|
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: staggered vs eclipsed conformers | Statement: [sawhorse projection, helpsDistinguish, staggered vs eclipsed conformers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpsDistinguish Context triple: [sawhorse projection, helpsDistinguish, staggered vs eclipsed conformers]
-
A.
helpsIdentify
chosen
Indicates a relationship where one entity serves to distinguish, recognize, or determine the identity or characteristics of another entity.
-
B.
aimsToDistinguish
Indicates an intention or effort by one entity to set itself or something else apart from others by highlighting differences or unique characteristics.
-
C.
distinction
Indicates that one entity is recognized, treated, or classified as different or separate from another.
-
D.
distinguishingTrait
Indicates that a particular characteristic or feature uniquely differentiates one entity from another.
-
E.
introducesDistinction
Indicates that one entity establishes or makes clear a conceptual or categorical difference between two or more entities or ideas.
- F. None of above.
Provenance (3 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_69ef5387e97c8190a9dab040d21cd048 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f62fb4f9688190a3ce7a1580436e35 |
completed | May 2, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69f62c1921008190a62675a31f66a875 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 1:37 p.m.