Triple
T17258130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kobayashi Issa |
E418936
|
entity |
| Predicate | pseudonym |
P39
|
FINISHED |
| Object | Issa |
E376878
|
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: Issa | Statement: [Kobayashi Issa, pseudonym, Issa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Issa Context triple: [Kobayashi Issa, pseudonym, Issa]
-
A.
Issa
chosen
Issa is a masculine given name of Arabic origin commonly used in various Middle Eastern and Muslim-majority cultures.
-
B.
Issa
Issa was an ancient Adriatic island settlement, known as a Greek colony and later Roman town off the coast of what is now Croatia.
-
C.
Manguissa
Manguissa is a Bantu language spoken by the Manguissa people in Cameroon.
-
D.
Hasana
Hasana is a small town in Egypt’s North Sinai Governorate, situated in the Sinai Peninsula.
-
E.
Dyula
Dyula is a Mande language widely used as a trade and lingua franca in parts of West Africa, particularly in Burkina Faso, Côte d’Ivoire, and Mali.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6ea7588190a94d222504a8cef5 |
completed | April 19, 2026, 1:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170ff6818819090077dc4a7b774ae |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:39 a.m.