Triple
T188143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senate of Chile |
E3660
|
entity |
| Predicate | buildingTypeOfSeat |
P1844
|
FINISHED |
| Object | legislative building |
—
|
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: legislative building | Statement: [Senate of Chile, buildingTypeOfSeat, legislative building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingTypeOfSeat Context triple: [Senate of Chile, buildingTypeOfSeat, legislative building]
-
A.
buildingType
chosen
Indicates the specific category or function that characterizes what kind of building something is.
-
B.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
C.
architectureType
Indicates the specific style or category of architecture that characterizes or defines an entity.
-
D.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
E.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2594abeec8190a48f36817e647fcd |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25672332081909386f35f3ca15dd2 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.