Triple
T15880175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diwaniyah |
E385054
|
entity |
| Predicate | isInCountryCapitalDistanceCategory |
P104574
|
FINISHED |
| Object | medium distance from Baghdad |
—
|
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: medium distance from Baghdad | Statement: [Diwaniyah, isInCountryCapitalDistanceCategory, medium distance from Baghdad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInCountryCapitalDistanceCategory Context triple: [Diwaniyah, isInCountryCapitalDistanceCategory, medium distance from Baghdad]
-
A.
isNearCapitalCity
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
-
B.
regionCapitalDistanceRelation
Indicates a relationship specifying the distance between a region and its capital.
-
C.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
D.
hasCountyCapitalDistance
Indicates a distance relationship specifying how far a county is from its capital.
-
E.
hasDistanceCategory
chosen
Indicates that one entity is associated with a qualitative or categorical classification of its distance relative to another entity or reference point.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142c3e18c8190bb7b023f4a0eaebb |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:51 a.m.