Triple
T23278935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tentena dialect |
E588802
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Tentena |
—
|
NE NERFINISHED |
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: Tentena | Statement: [Tentena dialect, spokenIn, Tentena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tentena Context triple: [Tentena dialect, spokenIn, Tentena]
-
A.
Tentena
chosen
Tentena is a small lakeside town in Central Sulawesi, Indonesia, known as a gateway to Lake Poso and the surrounding highland scenery.
-
B.
Tendeka
Tendeka is a central protagonist in Lauren Beukes's dystopian cyberpunk novel "Moxyland," known for his radical activism against a corporate-controlled police state.
-
C.
Tantallon
Tantallon is a small rural community located in southeastern Saskatchewan, Canada.
-
D.
Tantallon
Tantallon is a suburban community located outside Halifax, Nova Scotia, known as a residential and commercial hub for surrounding coastal and rural areas.
-
E.
Tentyra
Tentyra is the Greek name for the ancient Egyptian town of Iunet (modern Dendera), renowned for its temple complex dedicated to the goddess Hathor.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196419eac819081d0beb5767046dc |
completed | April 29, 2026, 5:25 a.m. |
Created at: April 17, 2026, 4:49 p.m.