Triple
T612868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romani |
E12137
|
entity |
| Predicate | selfDesignation |
P974
|
FINISHED |
| Object |
Rrom
Rrom is a self-designation used by some Romani people to refer to themselves and their ethnic community.
|
E76547
|
NE FINISHED |
How this triple was built (4 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: Rrom | Statement: [Romani, selfDesignation, Rrom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rrom Context triple: [Romani, selfDesignation, Rrom]
-
A.
ROM
ROM is a major museum in Toronto, Canada, renowned for its extensive collections in natural history, world cultures, and art.
-
B.
RM
RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
-
C.
ROM Library and Archives
ROM Library and Archives is the research and reference library of the Royal Ontario Museum, supporting scholarship on its collections, exhibitions, and related disciplines.
-
D.
OLEM
OLEM is a division of the U.S. Environmental Protection Agency responsible for overseeing land preservation, hazardous waste management, and emergency environmental response activities.
-
E.
RAN
RAN is the 3GPP working group responsible for specifying the radio access network technologies used in mobile communication systems such as LTE and 5G.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rrom Triple: [Romani, selfDesignation, Rrom]
Generated description
Rrom is a self-designation used by some Romani people to refer to themselves and their ethnic community.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rrom Target entity description: Rrom is a self-designation used by some Romani people to refer to themselves and their ethnic community.
-
A.
ROM
ROM is a major museum in Toronto, Canada, renowned for its extensive collections in natural history, world cultures, and art.
-
B.
RM
RM is the currency symbol that was used to denote the German Reichsmark, the former official currency of Germany from 1924 to 1948.
-
C.
ROM Library and Archives
ROM Library and Archives is the research and reference library of the Royal Ontario Museum, supporting scholarship on its collections, exhibitions, and related disciplines.
-
D.
OLEM
OLEM is a division of the U.S. Environmental Protection Agency responsible for overseeing land preservation, hazardous waste management, and emergency environmental response activities.
-
E.
RAN
RAN is the 3GPP working group responsible for specifying the radio access network technologies used in mobile communication systems such as LTE and 5G.
- F. None of above. chosen
Provenance (5 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. |
| NED1 | Entity disambiguation (via context triple) | batch_69a533dabe288190ab25bd6d76e79d06 |
completed | March 2, 2026, 6:53 a.m. |
| NEDg | Description generation | batch_69a54e4849f48190868d7b624e450dc3 |
completed | March 2, 2026, 8:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a55048e2ec81908d306f44b2ca24fa |
completed | March 2, 2026, 8:54 a.m. |
Created at: March 1, 2026, 7:35 p.m.