Triple
T9206558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sama people |
E220994
|
entity |
| Predicate | speakLanguage |
P741
|
FINISHED |
| Object | Sinama |
E700458
|
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: Sinama | Statement: [Sama people, speakLanguage, Sinama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sinama Context triple: [Sama people, speakLanguage, Sinama]
-
A.
Sinama
chosen
Sinama is an Austronesian language spoken by the Sama-Bajau people of the southern Philippines, Malaysia, and Indonesia.
-
B.
Sinana
Sinana is a district (woreda) in Ethiopia’s Oromia Region, located within the agriculturally important Bale Zone.
-
C.
Sikma
Sikma is a surname most notably associated with Jack Sikma, a Hall of Fame American basketball player known for his successful NBA career with the Seattle SuperSonics.
-
D.
Songo
Songo is a small town in Mozambique known primarily for its proximity to the Cahora Bassa Dam and its role in supporting the dam’s operations and nearby communities.
-
E.
Musiri
Musiri is a town in the Indian state of Tamil Nadu, known as an agricultural and commercial center situated along the Kaveri 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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd9b0b6788190908bee67a0c5d48f |
completed | April 1, 2026, 8:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d065e09fbc81908159b386038b3d73 |
completed | April 4, 2026, 1:14 a.m. |
Created at: March 30, 2026, 7:26 p.m.