Triple
T19964499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Largo do Calhariz |
E479893
|
entity |
| Predicate | hasNightlifeContextNearby |
P8175
|
FINISHED |
| Object | Bairro Alto nightlife area |
—
|
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: Bairro Alto nightlife area | Statement: [Largo do Calhariz, hasNightlifeContextNearby, Bairro Alto nightlife area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNightlifeContextNearby Context triple: [Largo do Calhariz, hasNightlifeContextNearby, Bairro Alto nightlife area]
-
A.
hasNightlifeArea
chosen
Indicates that a place contains or is associated with an area characterized by nightlife activities such as bars, clubs, or evening entertainment venues.
-
B.
offersNightlife
Indicates that a place provides opportunities for nighttime entertainment, such as bars, clubs, or evening events.
-
C.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
D.
nearbyVenue
Indicates that one venue is located close to another venue in physical space.
-
E.
isLocatedInCityWithClub
Indicates that an entity is situated in a city that has at least one (sports or similar) club based there.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc4417c8190912f3d85fd7a5a32 |
completed | April 20, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69e537f7e4848190b431a69ec3f1b609 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.