Triple
T34872950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Municipality of Campinas |
E1005799
|
entity |
| Predicate | hasTechPark |
P32590
|
FINISHED |
| Object | Techno Park Campinas |
—
|
NE NERFINISHED |
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: Techno Park Campinas | Statement: [Municipality of Campinas, hasTechPark, Techno Park Campinas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTechPark Context triple: [Municipality of Campinas, hasTechPark, Techno Park Campinas]
-
A.
hasSciencePark
chosen
Indicates that one entity possesses, hosts, or includes a science park associated with it.
-
B.
hasBusinessPark
Indicates that one entity possesses, contains, or is associated with a business park as part of its facilities or properties.
-
C.
hasIndustrialPark
Indicates that a location or entity possesses or contains an industrial park within its area or jurisdiction.
-
D.
hasIndustrialParkName
Indicates that an entity (such as an industrial park or related facility) bears or is identified by a specific industrial park name.
-
E.
hasInnovationHub
Indicates that an entity hosts, contains, or is associated with a dedicated center or facility focused on innovation activities.
- 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_69f76dbde1c08190a24e7f9beb564c8d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
Created at: May 3, 2026, 4 p.m.