Triple
T38349033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maykopsky District (de facto, without being part of it) |
E1041624
|
entity |
| Predicate | hasCapitalOfRegionNearby |
P41518
|
FINISHED |
| Object | Maykop |
—
|
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: Maykop | Statement: [Maykopsky District (de facto, without being part of it), hasCapitalOfRegionNearby, Maykop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCapitalOfRegionNearby Context triple: [Maykopsky District (de facto, without being part of it), hasCapitalOfRegionNearby, Maykop]
-
A.
regionCapitalNearby
chosen
Indicates that a capital city of a region is located close to the referenced place or entity.
-
B.
hasDepartmentCapitalNearby
Indicates that the subject entity has a departmental capital city located in close geographical proximity to it.
-
C.
connectsToRegionalCapital
Indicates that one location has a direct connection, such as a transport or administrative link, to a designated regional capital.
-
D.
countryCapitalNearby
Indicates that a country’s capital city is geographically close to a specified location or entity.
-
E.
isNearCapitalCity
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
- 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_69f76e2ad95481908c920c0e5c1c3e26 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a006417d1f4819093b2da02dbf2ab22 |
completed | May 10, 2026, 10:55 a.m. |
| PD | Predicate disambiguation | batch_6a00634a7a748190ac4774493fce3d30 |
completed | May 10, 2026, 10:51 a.m. |
Created at: May 3, 2026, 4:30 p.m.