Triple
T9953700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moe’s Tavern |
E195392
|
entity |
| Predicate | hasOccasionalEvent |
P91338
|
FINISHED |
| Object | karaoke night |
—
|
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: karaoke night | Statement: [Moe’s Tavern, hasOccasionalEvent, karaoke night]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOccasionalEvent Context triple: [Moe’s Tavern, hasOccasionalEvent, karaoke night]
-
A.
hadEvent
Indicates that an entity experienced, hosted, or was associated with a specific event at some point in time.
-
B.
hasDailyEvent
Indicates that an entity is associated with an event that occurs every day.
-
C.
hasPublicEventsIn
Indicates that an entity organizes or holds public events within a specified location or context.
-
D.
hasNotablePersonEvent
Indicates that there exists a significant event in which the person plays a notable or central role.
-
E.
hasEventFrequency
Indicates how often a particular event occurs within a given time period.
- F. None of above. chosen
Provenance (4 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb694b95481909d049302818e7137 |
completed | April 2, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69cd1d97c44081908730071269f07712 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd358386f48190833c862b5b8c04b2 |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:46 p.m.