Triple
T6925420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jarma Lewis |
E160293
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jarma |
E160293
|
NE 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: Jarma | Statement: [Jarma Lewis, givenName, Jarma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jarma Context triple: [Jarma Lewis, givenName, Jarma]
-
A.
Jarma
chosen
Jarma is a feminine given name most notably borne by American actress Jarma Lewis.
-
B.
Jamtha
Jamtha is a locality on the outskirts of Nagpur in Maharashtra, India, known primarily for hosting the Vidarbha Cricket Association Stadium.
-
C.
Gharaunda
Gharaunda is a town in the Indian state of Haryana known for its agricultural market and proximity to the historic city of Karnal.
-
D.
Jopara
Jopara is a mixed language spoken in Paraguay that blends Guaraní and Spanish in everyday communication.
-
E.
Jamaame
Jamaame is a significant urban and economic center in southern Somalia’s Jubaland region, known especially for its agricultural production and location along the Jubba River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6884d350081908d8a970e4d40ad78 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da18b6388190947dfc1eb9e5d382 |
completed | March 27, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7513fddd88190b99c4b7e3364d218 |
completed | March 28, 2026, 3:55 a.m. |
Created at: March 27, 2026, 2:26 p.m.