Triple
T16128573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Almond |
E391333
|
entity |
| Predicate | bitterVarietyContains |
P121584
|
FINISHED |
| Object | amygdalin |
—
|
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: amygdalin | Statement: [Almond, bitterVarietyContains, amygdalin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bitterVarietyContains Context triple: [Almond, bitterVarietyContains, amygdalin]
-
A.
bitterantType
Indicates the specific kind or category of bitterant used or associated with an entity.
-
B.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
-
C.
notableVarieties
Indicates that there are specific, distinguished types or versions associated with an entity that are recognized as notable.
-
D.
coffeeVariety
Indicates a relationship where a specific type or variety of coffee is associated with a coffee-related entity (such as a product, beverage, or plant).
-
E.
hasTasteIntensity
Indicates the degree or strength of taste associated with something.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20206a6f08190aa648d2bb11e7878 |
completed | April 17, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e183b9d3f08190953ada68f4272996 |
completed | April 17, 2026, 12:50 a.m. |
Created at: April 10, 2026, 5:01 a.m.