Triple
T5385203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plenary of the 40 chairs |
E120185
|
entity |
| Predicate | locationBuilding |
P36046
|
FINISHED |
| Object | headquarters of the Brazilian Academy of Letters |
—
|
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: headquarters of the Brazilian Academy of Letters | Statement: [Plenary of the 40 chairs, locationBuilding, headquarters of the Brazilian Academy of Letters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationBuilding Context triple: [Plenary of the 40 chairs, locationBuilding, headquarters of the Brazilian Academy of Letters]
-
A.
currentBuilding
chosen
Indicates that an entity is located in, associated with, or belongs to the building that is relevant in the current context.
-
B.
hasBuildingLocation
Indicates that a building is situated at, or associated with, a specific geographic or spatial location.
-
C.
building
Indicates that one entity constructs, assembles, or develops another entity, typically over a period of time.
-
D.
locationDescription
Indicates a textual description that specifies or characterizes the location of an entity.
-
E.
propertyLocation
Indicates the geographical place or address where a property is situated or found.
- 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_69bd46354c648190a38b26f107010a96 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd86f5a7388190aa4ba2052afca74e |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd8463a9c88190bd760378f3026180 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:03 p.m.