Triple
T612870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romani |
E12137
|
entity |
| Predicate | exonymStatus |
P17110
|
FINISHED |
| Object | often considered pejorative |
—
|
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: often considered pejorative | Statement: [Romani, exonymStatus, often considered pejorative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exonymStatus Context triple: [Romani, exonymStatus, often considered pejorative]
-
A.
hasExonym
Indicates that one entity is known by an alternative name or designation in another language or cultural context.
-
B.
hasDemonym
Indicates that one entity is the term (demonym) used to refer to the inhabitants or natives of another entity (typically a place).
-
C.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
-
D.
ethnonym
Indicates that one entity is the name of an ethnic group used to refer to the people associated with another entity.
-
E.
eraName
Indicates the named historical or chronological era associated with an entity or 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e08dbf88190ab050078a63e266b |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfa7b4481909bec7a5fd3e98c65 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49def31ec81909dc53e70f4a36eda |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.