Triple
T16567811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masa |
E402506
|
entity |
| Predicate | hasNeighboringLanguage |
P16383
|
FINISHED |
| Object | Mofu-Gudur |
E402507
|
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: Mofu-Gudur | Statement: [Masa, hasNeighboringLanguage, Mofu-Gudur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mofu-Gudur Context triple: [Masa, hasNeighboringLanguage, Mofu-Gudur]
-
A.
Mofu-Gudur
chosen
Mofu-Gudur is a Central Chadic language spoken primarily by the Mofu-Gudur people in northern Cameroon.
-
B.
Hofu
Hofu is a coastal city in western Honshu, Japan, known for its historic Hofu Tenmangu Shrine and industrial manufacturing base.
-
C.
Sugamo
Sugamo is a Tokyo neighborhood popularly known as the “Harajuku for old ladies,” famed for its Jizō-dōri shopping street and large elderly clientele.
-
D.
Gyoda
Gyoda is a historic city in eastern Japan known for its ancient rice paddies, traditional tabi sock production, and preserved castle town atmosphere.
-
E.
Mottama
Mottama is a historic port town in southeastern Myanmar, long known as Martaban, which was once an important trading center in the region.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35772f6608190a125c7d3c199c3e2 |
completed | April 18, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ee3dcbc819087ea66b262585232 |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5:16 a.m.