Triple
T23156333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gamba Osaka |
E578448
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Gamba |
—
|
NE NERFINISHED |
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: Gamba | Statement: [Gamba Osaka, nickname, Gamba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gamba Context triple: [Gamba Osaka, nickname, Gamba]
-
A.
Gamba
chosen
Gamba is a professional Japanese football club based in Suita, Osaka, competing in the J1 League.
-
B.
Gamba
Gamba is a coastal town in southwestern Gabon known for its oil industry and proximity to rich rainforest and marine ecosystems.
-
C.
Matoury
Matoury is a commune in French Guiana located near Cayenne, known for its role as a suburban and economic hub that includes part of the area surrounding the Guiana Space Centre.
-
D.
Kashiwa
Kashiwa is a city in Chiba Prefecture, Japan, known as a residential and commercial hub within the Greater Tokyo metropolitan area.
-
E.
Kashima Kikō
Kashima Kikō is a travel diary by the Japanese haiku master Matsuo Bashō, recounting his poetic journey to the Kashima Shrine and surrounding regions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245fb8de081908f0eba7b5fd75bc4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18efd598c81908fba9d583e30660e |
completed | April 29, 2026, 4:54 a.m. |
Created at: April 17, 2026, 4:01 p.m.