Triple
T30152279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WHOIS protocol |
E766425
|
entity |
| Predicate | queryModel |
P168486
|
FINISHED |
| Object | simple text query |
—
|
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: simple text query | Statement: [WHOIS protocol, queryModel, simple text query]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: queryModel Context triple: [WHOIS protocol, queryModel, simple text query]
-
A.
requestModel
Indicates that one entity asks another entity to provide or use a specific model for a task or interaction.
-
B.
queryEngineBasedOn
Indicates that something is determined, implemented, or operates using a particular query engine as its underlying basis.
-
C.
namespaceModel
Indicates a relationship where a model is defined within, or associated with, a particular namespace or logical grouping.
-
D.
dataModel
Indicates a relationship where an entity defines, uses, or is structured according to a specific data model or schema.
-
E.
modelIn
Indicates that one entity serves as a representation or simulation of another entity.
- 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_69f22479cd088190ab4c6f3fce39d1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67ed4df5081908d1431e3a1a1fb0e |
completed | May 2, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69f673c7a4588190837854f3ef61e6bf |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f6749f205c81909d1aacf462912eee |
completed | May 2, 2026, 10:03 p.m. |
Created at: April 29, 2026, 7:20 p.m.