Triple
T12155697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senegambian languages |
E289568
|
entity |
| Predicate | hasNotableLanguage |
P7390
|
FINISHED |
| Object | Papel |
E151361
|
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: Papel | Statement: [Senegambian languages, hasNotableLanguage, Papel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Papel Context triple: [Senegambian languages, hasNotableLanguage, Papel]
-
A.
Papel
chosen
Papel is an indigenous language of Guinea-Bissau spoken primarily by the Papel people in the coastal regions around Bissau.
-
B.
Papper
Papper is one of the islands in the Hvaler archipelago in southeastern Norway, known for its coastal scenery and holiday cottages.
-
C.
Liquid Paper
Liquid Paper is a popular correction fluid product used to cover and correct handwritten or typed errors on paper.
-
D.
The Paper
The Paper is a 1994 American comedy-drama film directed by Ron Howard that follows the hectic, deadline-driven day at a New York City tabloid newspaper.
-
E.
Pensil
Pensil is a neighborhood located within the Miguel Hidalgo borough of Mexico City, Mexico.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915c1673c8190830cd15525d16869 |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f69c8d408190abbc900deb534045 |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:50 p.m.