Triple
T35013488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arenthia |
E1009992
|
entity |
| Predicate | borderCityBetween |
P85379
|
FINISHED |
| Object | Valenwood |
—
|
NE NERFINISHED |
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 | Statement: [Arenthia, borderCityBetween, Valenwood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderCityBetween Context triple: [Arenthia, borderCityBetween, Valenwood]
-
A.
shareMajorBorderCities
chosen
Indicates that two regions or countries have a shared border along which there are one or more major cities situated on or near that boundary.
-
B.
borderCityStatus
Indicates that a city holds a designated status due to its location on or near a political or geographic border.
-
C.
borderedBy
Indicates that one entity shares a common boundary or edge with another entity.
-
D.
borderCityOnUSSide
Indicates that a city is located on the U.S. side of an international border shared with another country.
-
E.
borderTownAcrossBorder
Indicates that a town lies on one side of a border directly opposite or adjacent to a town on the other side of that border.
- 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff90b673248190b4dda9e005642d17 |
completed | May 9, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69ff8d5bee1081909274052945e98a6f |
completed | May 9, 2026, 7:39 p.m. |
Created at: May 3, 2026, 4:01 p.m.