Triple
T16654988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enda Mariam Cathedral |
E404703
|
entity |
| Predicate | locatedInUrbanContext |
P82630
|
FINISHED |
| Object | Asmara city center |
—
|
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: Asmara city center | Statement: [Enda Mariam Cathedral, locatedInUrbanContext, Asmara city center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInUrbanContext Context triple: [Enda Mariam Cathedral, locatedInUrbanContext, Asmara city center]
-
A.
isInUrbanContext
chosen
Indicates that something exists, occurs, or is situated within an urban or city-based environment or setting.
-
B.
withinUrbanArea
Indicates that one entity is located inside the spatial boundaries of an urban area associated with another entity.
-
C.
locatedInUrbanizationType
Indicates that one entity is situated within, or belongs to, a specific type or category of urbanized area (e.g., city, suburb, metropolitan zone).
-
D.
appliesToUrbanArea
Indicates that the relationship, rule, or condition is specifically relevant or applicable to an urban area.
-
E.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37bfa45d8819081bf8579a7160389 |
completed | April 18, 2026, 12:41 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.