Triple
T36881631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Cehegín |
E911493
|
entity |
| Predicate | hasOldTownArchitecture |
P186640
|
FINISHED |
| Object | medieval architecture |
—
|
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: medieval architecture | Statement: [City of Cehegín, hasOldTownArchitecture, medieval architecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOldTownArchitecture Context triple: [City of Cehegín, hasOldTownArchitecture, medieval architecture]
-
A.
hasCenturyOldArchitecture
Indicates that something features architecture that is at least one hundred years old.
-
B.
isFromCityWithHistoricArchitecture
Indicates that an entity originates from a city known for its historically significant or architecturally notable buildings and structures.
-
C.
hasColonialArchitecture
Indicates that something features or exhibits architectural characteristics associated with colonial-era design or construction.
-
D.
hasPreservedBuildings
Indicates that an entity possesses buildings that have been maintained or kept in their original or historical condition.
-
E.
hasHistoricTownSquare
Indicates that an entity possesses or includes a town square that is of historical significance.
- F. None of above. chosen
Provenance (4 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_69f76e82339881909607a65c0503d941 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:13 p.m.