Triple
T3480054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niflheim |
E73466
|
entity |
| Predicate | numberOfRealmsContext |
P49017
|
FINISHED |
| Object | one of the Nine Worlds in some traditions |
—
|
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: one of the Nine Worlds in some traditions | Statement: [Niflheim, numberOfRealmsContext, one of the Nine Worlds in some traditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRealmsContext Context triple: [Niflheim, numberOfRealmsContext, one of the Nine Worlds in some traditions]
-
A.
numberOfInstances
Indicates the quantity or count of distinct occurrences or instances associated with a given entity or context.
-
B.
numberOfDomes
Indicates the quantity of domes that an entity possesses or is associated with.
-
C.
numberOfRegions
Indicates the total count of distinct regions associated with or contained within a given entity.
-
D.
numberOfTerritories
Indicates the total count of territories associated with a given entity.
-
E.
numberOfTerminals
Indicates the total count of terminal points or endpoints associated with an entity.
- 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_69ad85b3c9b08190857cae74c7f36da9 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb7461708190898002fbd1191f34 |
completed | March 8, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69adae0935ac8190bfa8a8bd3dcd3301 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb1ecb02881908394f197e31431b4 |
completed | March 8, 2026, 5:29 p.m. |
Created at: March 8, 2026, 3:17 p.m.