Triple
T6195778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wajo Regency |
E138504
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Wajo |
E518372
|
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: Wajo | Statement: [Wajo Regency, namedAfter, Wajo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wajo Context triple: [Wajo Regency, namedAfter, Wajo]
-
A.
Wajo
chosen
Wajo was a historical kingdom and trading polity in what is now South Sulawesi, Indonesia, known for its influential Bugis culture and maritime commerce.
-
B.
Takashima
Takashima is a lakeside city in western Shiga Prefecture, Japan, known for its scenic location along Lake Biwa and surrounding mountains.
-
C.
Takashima
Takashima is a prominent commercial and waterfront district in Nishi-ku, Yokohama, known for major shopping complexes and modern urban development.
-
D.
Tatsuno
Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
-
E.
Sagamu
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.
- 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_69c008ab9b3081908a11b2c744838435 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0624571508190bd273b4a051fbe41 |
completed | March 22, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20d8e4b308190b855cb04c9cfefeb |
completed | March 24, 2026, 4:05 a.m. |
Created at: March 22, 2026, 4:20 p.m.