Triple
T7165163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lusoponte |
E167047
|
entity |
| Predicate | hasConcessionRole |
P37449
|
FINISHED |
| Object | design |
—
|
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: design | Statement: [Lusoponte, hasConcessionRole, design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConcessionRole Context triple: [Lusoponte, hasConcessionRole, design]
-
A.
hasConcessions
Indicates that one entity provides or contains concession facilities, services, or rights (such as food, drink, or merchandise sales) for another entity or within a given context.
-
B.
hasConcessionaire
chosen
Indicates that one entity is designated as the concessionaire (holder of operating or usage rights under a concession) for another entity.
-
C.
hasCapitalRole
Indicates that an entity holds an official role, function, or status specifically associated with a capital city.
-
D.
hasNotableRoleIn
Indicates that an entity holds a significant or noteworthy role or function within another entity, event, work, or context.
-
E.
concessionType
Indicates the specific kind or category of concession (such as a discount, exemption, or special allowance) that applies in a given context.
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e832d2548190aacff0de80dbc268 |
completed | March 27, 2026, 8:27 p.m. |
| PD | Predicate disambiguation | batch_69c6e1cd5c948190a9113b23f7308c21 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:47 p.m.