Triple
T16891185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boaco Department |
E424174
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Camoapa |
E604687
|
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: Camoapa | Statement: [Boaco Department, hasSettlement, Camoapa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Camoapa Context triple: [Boaco Department, hasSettlement, Camoapa]
-
A.
Camoapa
chosen
Camoapa is a municipality in central Nicaragua known for its cattle ranching, dairy production, and traditional rural culture.
-
B.
Cambo
Cambo is a film producer associated with projects featuring actress Amala in Indian cinema.
-
C.
Kafanchan
Kafanchan is a major town in southern Kaduna State, Nigeria, known as a key railway junction and commercial hub for the surrounding region.
-
D.
Nakamaro
Nakamaro is a Japanese given name historically associated with figures such as the Nara-period court noble and poet Ōtomo no Yakamochi’s contemporary, Fujiwara no Nakamaro.
-
E.
Pakurumo
Pakurumo is a popular Afrobeat song by Nigerian artist Wizkid, known for its upbeat rhythm and dance-friendly vibe.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3bbc473d4819090cfea374ef5ca49 |
completed | April 18, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c7a7fd8481908ef82a13418b1c2d |
completed | May 10, 2026, 6 p.m. |
Created at: April 10, 2026, 5:29 a.m.