Triple
T11293867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geococcyx |
E267397
|
entity |
| Predicate | vernacularNameOf |
P80396
|
FINISHED |
| Object | roadrunner |
—
|
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: roadrunner | Statement: [Geococcyx, vernacularNameOf, roadrunner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vernacularNameOf Context triple: [Geococcyx, vernacularNameOf, roadrunner]
-
A.
vernacularOf
Indicates that one language or dialect is the everyday, locally used form corresponding to another, more general or standard language.
-
B.
vernacularNameAppliedTo
chosen
Indicates that a particular common or vernacular name is assigned or applied to an entity.
-
C.
vernacularGroup
Indicates a relationship where entities are grouped or associated based on sharing the same vernacular (local or commonly spoken) language.
-
D.
multilingualName
Indicates that an entity has one or more names expressed in multiple natural languages.
-
E.
languageCommonlyCalled
Indicates that one language is commonly referred to or known by a particular alternative name or label.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e98b149481909f432a6b9ef8bfbb |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d787a6ca2c8190afdc24b61ccd3f8a |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.