Triple
T15928930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Poso |
E386273
|
entity |
| Predicate | locatedNearTown |
P3883
|
FINISHED |
| Object | Tentena |
E1181282
|
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: Tentena | Statement: [Lake Poso, locatedNearTown, Tentena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tentena Context triple: [Lake Poso, locatedNearTown, 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.
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.
-
C.
Tantolunden
Tantolunden is a large park and recreational area in Stockholm known for its allotment gardens, waterfront, and outdoor activities.
-
D.
Taborio
Taborio is a village settlement located on the island of Nonouti in the Republic of Kiribati.
-
E.
Tadoe
Tadoe is an American rapper from Chicago known for his involvement in the drill music scene and frequent collaborations with artists like Chief Keef and Young Chop.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156a39abc8190927818f6e185033a |
completed | April 16, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5b0833081909668c042234b5b75 |
completed | May 9, 2026, 10:31 p.m. |
Created at: April 10, 2026, 4:52 a.m.