Triple
T24781652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Theatre of Cartagena |
E620009
|
entity |
| Predicate | museumDesigner |
P14560
|
FINISHED |
| Object | Rafael Moneo |
—
|
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: Rafael Moneo | Statement: [Roman Theatre of Cartagena, museumDesigner, Rafael Moneo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: museumDesigner Context triple: [Roman Theatre of Cartagena, museumDesigner, Rafael Moneo]
-
A.
exhibitionDesigner
Indicates that an entity is responsible for planning, organizing, and designing the layout and presentation of an exhibition for another entity or event.
-
B.
museumConversionArchitect
chosen
Indicates that an architect was responsible for converting an existing structure into a museum.
-
C.
mainMonumentDesigner
Indicates that one entity is the primary architect or designer responsible for the creation or design of a particular monument.
-
D.
museumFocus
Indicates that a museum is primarily dedicated to or specializes in a particular subject, theme, or type of collection.
-
E.
museumSection
Indicates that one entity is a section, area, or subdivision within a museum associated with the other entity.
- 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_69e2fabdbe8c8190adbb9434b8636cad |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410d73b288190995b2ada5788f436 |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 4:44 a.m.