Triple
T5682746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Consulta |
E125234
|
entity |
| Predicate | seatBuildingFunction |
P65754
|
FINISHED |
| Object | historic palace and institutional seat |
—
|
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: historic palace and institutional seat | Statement: [Consulta, seatBuildingFunction, historic palace and institutional seat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatBuildingFunction Context triple: [Consulta, seatBuildingFunction, historic palace and institutional seat]
-
A.
buildingStructure
Indicates that one entity is a structural component or physical part that forms, supports, or constitutes the construction of another entity.
-
B.
buildingSection
Indicates a relationship where one entity is a specific section, part, or subdivision of a larger building.
-
C.
buildingComplex
Indicates a relationship where multiple buildings are grouped and function together as a single integrated complex.
-
D.
building
Indicates that one entity constructs, assembles, or develops another entity, typically over a period of time.
-
E.
facesBuilding
Indicates that one building is oriented toward and directly faces another building.
- 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_69c0082a884c8190a79001bae658941f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0248751bc8190b12aaa42d1ef17e3 |
completed | March 22, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69c021be59088190a81c880957f666ab |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c024861bc88190a17782c1982fbb3e |
completed | March 22, 2026, 5:19 p.m. |
Created at: March 22, 2026, 3:44 p.m.