Triple
T8974912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kore |
E214361
|
entity |
| Predicate | consequenceOfFood |
P86018
|
FINISHED |
| Object | obliged to spend part of year in underworld |
—
|
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: obliged to spend part of year in underworld | Statement: [Kore, consequenceOfFood, obliged to spend part of year in underworld]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consequenceOfFood Context triple: [Kore, consequenceOfFood, obliged to spend part of year in underworld]
-
A.
usesFood
Indicates that one entity employs or consumes a food item as a resource, ingredient, or means to achieve some purpose.
-
B.
foodEffect
Indicates how consuming a particular food influences or changes another entity, such as an organism, condition, or process.
-
C.
mainFoodAffected
Indicates that a primary or central food item is directly impacted or influenced by a specified action or condition.
-
D.
eatenAs
Indicates that one entity is consumed or used as food by another entity.
-
E.
largelyConsumedBy
Indicates that something is mostly or predominantly eaten or used up by a particular consumer or group.
- 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_69ca839dbf608190a2f5990477115d29 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6784d1808190899c980f76084ff8 |
completed | April 1, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed9a2d48190ad11381078e823b7 |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5fcf24348190b6b845205161c0ee |
completed | March 31, 2026, 11:59 p.m. |
Created at: March 30, 2026, 7:02 p.m.