Triple
T33398485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whatever/Whenever concierge service |
E855231
|
entity |
| Predicate | typicalRequestType |
P79829
|
FINISHED |
| Object | restaurant reservations |
—
|
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: restaurant reservations | Statement: [Whatever/Whenever concierge service, typicalRequestType, restaurant reservations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRequestType Context triple: [Whatever/Whenever concierge service, typicalRequestType, restaurant reservations]
-
A.
requestType
chosen
Indicates the specific kind or category of request being made in an interaction or transaction.
-
B.
typicalTargetType
Indicates the usual or most common type or category of entity that serves as the target or recipient in a given relationship or action.
-
C.
typicalRequirement
Indicates that one entity is a standard or commonly expected prerequisite, condition, or necessity for another entity.
-
D.
requirementType
Indicates the specific category or classification of a given requirement within a broader requirements framework or system.
-
E.
typicalVisitType
Indicates the usual or most common category of visit associated with an entity or event.
- 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_69f3496e3f1c8190bcecfa82aa9d17ff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:35 a.m.