Triple
T34005431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hooka |
E871946
|
entity |
| Predicate | hasIntendedSetting |
P151428
|
FINISHED |
| Object | nightclubs |
—
|
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: nightclubs | Statement: [Hooka, hasIntendedSetting, nightclubs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntendedSetting Context triple: [Hooka, hasIntendedSetting, nightclubs]
-
A.
hasSetting
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
-
B.
originalIntendedSetting
chosen
Indicates the context, environment, or circumstances for which something was initially designed or meant to be used.
-
C.
hasSettingBy
Indicates that something (such as a work, event, or scenario) has its contextual environment, location, or background defined or established by a particular agent or source.
-
D.
hasUserSetting
Indicates that a user is associated with a specific configuration or preference setting.
-
E.
hasIntendedEffect
Indicates that one entity is expected or designed to produce a particular effect or outcome on another entity or 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_69f349a08848819084b348d64c1879c3 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a000efe971081909de03f875a7ad6cc |
completed | May 10, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_6a000c4ffe788190a5757af60aadd9f3 |
completed | May 10, 2026, 4:40 a.m. |
Created at: May 1, 2026, 1:50 a.m.