Triple
T37697706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanish |
E938972
|
entity |
| Predicate | hasUsageMode |
P11331
|
FINISHED |
| Object | pre-treatment of stains |
—
|
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: pre-treatment of stains | Statement: [Vanish, hasUsageMode, pre-treatment of stains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUsageMode Context triple: [Vanish, hasUsageMode, pre-treatment of stains]
-
A.
hasUsageLevel
Indicates the degree or intensity with which something is used or utilized.
-
B.
usedOnMode
chosen
Indicates that something is applied, operated, or functions specifically in a given mode or operational setting.
-
C.
hasUsageRegister
Indicates that a linguistic expression is associated with a particular usage register or level of formality in communication.
-
D.
hasUsageNote
Indicates that there is an associated explanatory note describing how or when something should be used.
-
E.
hasModeSystem
Indicates that one entity operates under, or is associated with, a particular mode defined or managed by another system.
- 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_69f76eda6ae48190b3111071eeacc038 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.