Triple
T12711974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Remo |
E303740
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object | Sagamu |
E348934
|
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: Sagamu | Statement: [Remo, hasMajorTown, Sagamu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sagamu Context triple: [Remo, hasMajorTown, Sagamu]
-
A.
Sagamu
chosen
Sagamu is a major town and commercial center in southwestern Nigeria known for its kola nut trade and location along key transport routes in Ogun State.
-
B.
Tatsuno
Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
-
C.
Tagawa
Tagawa is a small inland city in Japan known historically as a coal-mining center within Fukuoka Prefecture on Kyushu Island.
-
D.
Isahaya
Isahaya is a city in southwestern Japan known for its agricultural production, historical flood-control projects, and proximity to Nagasaki City.
-
E.
Sodegaura
Sodegaura is a coastal city in Chiba Prefecture, Japan, known for its industrial waterfront, proximity to Tokyo Bay, and role within the Keiyō industrial zone.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96208fa6481909d6fd43654752a2d |
completed | April 10, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f0a5a58819082111550a65a04b9 |
completed | May 3, 2026, 10:10 a.m. |
Created at: April 9, 2026, 5:23 p.m.