Triple
T6811089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lúcio Costa |
E156633
|
entity |
| Predicate | roleInBrasília |
P8234
|
FINISHED |
| Object | chief urban planner |
—
|
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: chief urban planner | Statement: [Lúcio Costa, roleInBrasília, chief urban planner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInBrasília Context triple: [Lúcio Costa, roleInBrasília, chief urban planner]
-
A.
roleInBrazil
Indicates that an entity holds or held a specific role, position, or function within the context of Brazil.
-
B.
roleInPortugal
Indicates that an entity holds or has held a specific role, position, or function within the context of Portugal.
-
C.
roleInCanberra
Indicates that an entity holds or performs a specific role, position, or function within the context of Canberra.
-
D.
urbanAreaRankInBrazil
Indicates the relative position or ranking of an urban area compared to other urban areas within Brazil.
-
E.
hasCityRole
chosen
Indicates that an entity holds or is assigned a specific role, function, or status within a particular city.
- 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d327e37081909d576e6eff9eec97 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09bb4f881909bf20c188cb3e8e1 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:16 p.m.