Triple
T14400901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Einherjar |
E357066
|
entity |
| Predicate | foodConsumed |
P46445
|
FINISHED |
| Object | meat of the boar Sæhrímnir |
—
|
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: meat of the boar Sæhrímnir | Statement: [Einherjar, foodConsumed, meat of the boar Sæhrímnir]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foodConsumed Context triple: [Einherjar, foodConsumed, meat of the boar Sæhrímnir]
-
A.
intendedFood
Indicates that one entity is the food item that another entity plans or is meant to eat or consume.
-
B.
usesFood
Indicates that one entity employs or consumes a food item as a resource, ingredient, or means to achieve some purpose.
-
C.
eatenAs
chosen
Indicates that one entity is consumed or used as food by another entity.
-
D.
foodItem
Indicates that one entity is a food item that can be eaten or used as food in relation to another entity.
-
E.
eatingHabit
Indicates a characteristic pattern or regularity in how an entity consumes food, such as what, when, or how it typically eats.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de908500048190bb6a20fe318d5c62 |
completed | April 14, 2026, 7:07 p.m. |
| PD | Predicate disambiguation | batch_69de2aa024c48190805df6a9d63deb10 |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:17 a.m.