Triple
T8686768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orma |
E206178
|
entity |
| Predicate | glottologName |
P6521
|
FINISHED |
| Object | Orma |
E206178
|
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: Orma | Statement: [Orma, glottologName, Orma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orma Context triple: [Orma, glottologName, Orma]
-
A.
Orma
chosen
Orma is a major dialect of the Oromo language spoken primarily by the Orma people of Kenya.
-
B.
Ormur
Ormur is a lesser-known Eastern Iranian language spoken primarily by the Ormur people in parts of Afghanistan and Pakistan.
-
C.
Ommen
Ommen is a small historic town and municipality in the Dutch province of Overijssel, known for its scenic river landscapes and tourism.
-
D.
Gouraya
Gouraya is a coastal town in northern Algeria known for its Mediterranean shoreline and proximity to the Gouraya National Park’s rugged landscapes.
-
E.
Karosta
Karosta is a historic former military port district in the Latvian city of Liepāja, known for its Tsarist-era fortifications, Soviet naval heritage, and distinctive coastal landscape.
- 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_69ca835481fc819084e33d3bc883bfa6 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef3cd888c81909fb1ece99988db36 |
completed | April 2, 2026, 10:55 p.m. |
Created at: March 30, 2026, 6:33 p.m.