Triple
T3049571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palace of Conventions, Havana |
E83533
|
entity |
| Predicate | hasCatering |
P22897
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Palace of Conventions, Havana, hasCatering, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCatering Context triple: [Palace of Conventions, Havana, hasCatering, yes]
-
A.
hasCharacterDining
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
-
B.
hasSpecialMeal
Indicates that an entity provides, is assigned, or is associated with a designated special meal option.
-
C.
hasMealType
Indicates that an entity is associated with a specific category or type of meal (such as breakfast, lunch, or dinner).
-
D.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
-
E.
hasHospitalityComponent
chosen
Indicates that something includes, involves, or is associated with a hospitality-related element, service, or function.
- 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_69ad8b24924c8190a9bb6f61d519e4ae |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9bb00a348190877c9cbf0f13cba4 |
completed | March 8, 2026, 3:54 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.