Triple
T36571429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | atmospheric pressure chemical ionization |
E902131
|
entity |
| Predicate | sampleIntroduction |
P185875
|
FINISHED |
| Object | liquid effluent from LC |
—
|
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: liquid effluent from LC | Statement: [atmospheric pressure chemical ionization, sampleIntroduction, liquid effluent from LC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sampleIntroduction Context triple: [atmospheric pressure chemical ionization, sampleIntroduction, liquid effluent from LC]
-
A.
sectionIntroduced
Indicates that a particular section was introduced or added at a specific point in time or context.
-
B.
hasIntroduction
Indicates that one entity includes or provides an introductory section, part, or presentation for another entity.
-
C.
sampleUsage
Indicates that an entity is used as an example or illustration to demonstrate how something works or is applied.
-
D.
hasIntro
Indicates that an entity includes or is associated with an introductory section or opening part.
-
E.
introductionContext
Indicates the situational or background circumstances under which an introduction between entities takes place.
- 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_69f76e6416708190a9754b8c52d4e453 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1baf25c8190a78dd54a400d2c50 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c3705b5c81908c84004543a71c07 |
completed | May 3, 2026, 9:51 p.m. |
Created at: May 3, 2026, 4:11 p.m.