Triple
T7236089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irwin mango |
E155229
|
entity |
| Predicate | eatingQuality |
P32634
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Irwin mango, eatingQuality, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eatingQuality Context triple: [Irwin mango, eatingQuality, high]
-
A.
hasCookingQuality
chosen
Indicates that something possesses a particular characteristic or attribute related to cooking, such as flavor, texture, or suitability for a cooking method.
-
B.
meatQuality
Indicates the assessed level or characteristics of quality associated with a given piece or type of meat.
-
C.
eatingPermitted
Indicates that an entity is allowed or authorized to eat in a given context or situation.
-
D.
isEatenIn
Indicates that one entity (typically food) is consumed within the context, location, or occasion specified by another entity.
-
E.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
- 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_69c688143bfc81908d4176617735e601 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea552a688190a00f5d0ad982f787 |
completed | March 27, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69c6e7644648819096a5e2de5d0dbe97 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:55 p.m.