Triple
T16751627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beti–Pahuin languages |
E407094
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object | Manguissa |
E1200464
|
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: Manguissa | Statement: [Beti–Pahuin languages, hasLanguage, Manguissa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manguissa Context triple: [Beti–Pahuin languages, hasLanguage, Manguissa]
-
A.
Manguissa
chosen
Manguissa is a Bantu language spoken by the Manguissa people in Cameroon.
-
B.
Moussa
Moussa is the protagonist of the work "Child of Fortune," around whom the story’s central events and character development revolve.
-
C.
Mamoudou
Mamoudou is a masculine given name of West African origin, notably borne by Mauritanian-American actor Mamoudou Athie.
-
D.
Si Moussa
Si Moussa was a powerful 19th-century grand vizier of Morocco who served under Sultan Hassan I and commissioned the opulent Bahia Palace in Marrakech.
-
E.
Hamidou
Hamidou is a brutal Turkish prison guard and primary antagonist in the film "Midnight Express."
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa271de48190b4a535408aeef734 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a52402848190b029cb0be31b4c74 |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.