Triple
T14168891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argungu Fishing Festival |
E351151
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Argungu |
E733803
|
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: Argungu | Statement: [Argungu Fishing Festival, locatedIn, Argungu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Argungu Context triple: [Argungu Fishing Festival, locatedIn, Argungu]
-
A.
Argungu
chosen
Argungu is a town in northwestern Nigeria renowned for its annual international fishing and cultural festival.
-
B.
Guraru
Guraru is a town in the Indian state of Bihar, known as a local settlement within the Gaya region.
-
C.
Itumbiara
Itumbiara is a municipality in the Brazilian state of Goiás, known for its strategic location on the Paranaíba River and its role as a regional economic and transportation hub.
-
D.
Ngola
Ngola is an alternative name for the Angolar people, a community of African descent primarily associated with São Tomé and Príncipe.
-
E.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b472288190b4a271daa54aa6cd |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7f779248190921c85f99f587296 |
completed | May 7, 2026, 8:37 p.m. |
Created at: April 10, 2026, 1 a.m.