Triple
T23143705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Orcines |
E577529
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Chanat |
—
|
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: Chanat | Statement: [canton of Orcines, contains, Chanat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chanat Context triple: [canton of Orcines, contains, Chanat]
-
A.
Chanat
chosen
Chanat is a small commune in central France’s Puy-de-Dôme department, known for its rural setting in the Auvergne region near the spa town of Châtel-Guyon.
-
B.
Chinnha
Chinnha is a notable literary work by the influential Bengali writer Manik Bandopadhyay.
-
C.
Chatan
Chatan is a coastal town in central Okinawa, Japan, known for its American Village entertainment district and proximity to several U.S. military bases.
-
D.
Chetlat
Chetlat is a small inhabited coral island in the Lakshadweep archipelago of India, known for its coconut cultivation, fishing, and surrounding lagoon.
-
E.
Chanura
Chanura is a powerful demon warrior in Hindu mythology who serves the tyrant king Kamsa and is ultimately slain by Krishna.
- 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_69e245f8e6248190ba3d58e068b4dccb |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18ecc3710819088ac5d72dad0459a |
completed | April 29, 2026, 4:53 a.m. |
Created at: April 17, 2026, 4 p.m.