Triple
T32786090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | When It Rains It Pours |
E838501
|
entity |
| Predicate | targetProductFeature |
P103513
|
FINISHED |
| Object | anti-caking properties |
—
|
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: anti-caking properties | Statement: [When It Rains It Pours, targetProductFeature, anti-caking properties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetProductFeature Context triple: [When It Rains It Pours, targetProductFeature, anti-caking properties]
-
A.
productCharacteristic
chosen
Indicates that a product possesses, exhibits, or is defined by a specific characteristic or attribute.
-
B.
targetFeature
Indicates that one entity is the specific feature, attribute, or characteristic that another entity is directed toward, focused on, or intended to affect.
-
C.
brandFeatures
Indicates that a brand includes, offers, or is characterized by a particular feature or attribute.
-
D.
featuresItem
Indicates that one entity includes, presents, or highlights another entity as a notable item or component.
-
E.
catalogCharacteristic
Indicates that a catalog has a specific characteristic or attribute associated with it.
- 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_69f3493b83f48190be335cd42465cecf |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe189fec148190aeef51b417ba15b0 |
completed | May 8, 2026, 5:08 p.m. |
| PD | Predicate disambiguation | batch_69fe17285b0881908de7569d8dbd20bd |
completed | May 8, 2026, 5:02 p.m. |
Created at: May 1, 2026, 1:14 a.m.