Triple
T1117241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cerro district of Havana |
E11127
|
entity |
| Predicate | buildingCondition |
P25131
|
FINISHED |
| Object | aging |
—
|
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: aging | Statement: [Cerro district of Havana, buildingCondition, aging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingCondition Context triple: [Cerro district of Havana, buildingCondition, aging]
-
A.
constructionType
Indicates the specific method or style by which something is built or constructed.
-
B.
builtProperty
Indicates that a constructed structure or building has been created on, or is associated with, a particular property or piece of land.
-
C.
building
Indicates that one entity constructs, assembles, or develops another entity, typically over a period of time.
-
D.
buildingSection
Indicates a relationship where one entity is a specific section, part, or subdivision of a larger building.
-
E.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
- 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_69a493252a648190ac48f8742474a5e8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4562f48190831e959f5f309956 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc47fce48190825d3a877251f789 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:43 p.m.