Triple
T11047644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baranduin |
E261172
|
entity |
| Predicate | separatesRegionFromRegion |
P85284
|
FINISHED |
| Object | the Shire and the Old Forest |
—
|
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: the Shire and the Old Forest | Statement: [Baranduin, separatesRegionFromRegion, the Shire and the Old Forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: separatesRegionFromRegion Context triple: [Baranduin, separatesRegionFromRegion, the Shire and the Old Forest]
-
A.
separatedAsRegion
Indicates that one entity is distinguished or partitioned from others as a distinct region or area.
-
B.
separatesLinguisticRegions
Indicates that one entity serves as a boundary or divider between distinct linguistic regions or language areas.
-
C.
separatesTerritoryOf
chosen
Indicates that one entity serves as a boundary or divider between the territories or domains of two other entities.
-
D.
separatesAdministrativeUnits
Indicates that one entity serves as a boundary or divider that distinguishes or splits different administrative units from each other.
-
E.
separatesState
Indicates that one entity serves as a dividing boundary or barrier between two distinct states or regions.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798315b988190bc565581b2664009 |
completed | April 9, 2026, 12:14 p.m. |
| PD | Predicate disambiguation | batch_69d74407cb088190ba37c8da3d342b64 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:26 p.m.