Triple
T35013817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bosmeris |
E1009999
|
entity |
| Predicate | primaryRegionInLore |
P109542
|
FINISHED |
| Object | Valenwood forests |
E2123599
|
NE 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: Valenwood forests | Statement: [Bosmeris, primaryRegionInLore, Valenwood forests]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryRegionInLore Context triple: [Bosmeris, primaryRegionInLore, Valenwood forests]
-
A.
culturalRegionOfLore
chosen
Indicates that a particular cultural region is the primary setting, origin, or contextual background for a given body of lore or tradition.
-
B.
primaryRegionDepicted
Indicates that a resource primarily depicts or visually represents a particular geographic or spatial region as its main subject.
-
C.
countryInLore
Indicates that a country exists or is referenced within the fictional or narrative lore of a given universe or setting.
-
D.
fictionalSettingRegion
Indicates that a fictional setting is located within or associated with a specific geographic or administrative region.
-
E.
coreRegionOf
Indicates that one entity constitutes the central or most essential part of another entity’s structure, area, or domain.
- F. None of above.
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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37d93d6ae8819083158efbf899eb0c |
completed | June 21, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.