Triple
T11996882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yusuf |
E285553
|
entity |
| Predicate | collaboratesWith |
P37
|
FINISHED |
| Object | Saito |
E339085
|
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: Saito | Statement: [Yusuf, collaboratesWith, Saito]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saito Context triple: [Yusuf, collaboratesWith, Saito]
-
A.
Saito
chosen
Saito is a Japanese surname commonly borne by notable figures in fields such as politics, sports, and the arts.
-
B.
Tateishi
Tateishi is a neighborhood in Tokyo known for its traditional shitamachi atmosphere, narrow shopping streets, and old-style bars and eateries.
-
C.
Sugimoto
Sugimoto is a Japanese surname borne by various notable individuals across fields such as art, sports, and academia.
-
D.
Hiranaka
Hiranaka is a Japanese surname borne by individuals such as former professional boxer Akinobu Hiranaka.
-
E.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c172788190b92042e9d10a48bf |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8b788308190bd9c3b68569bc56a |
completed | May 3, 2026, 2:53 a.m. |
Created at: April 8, 2026, 9:46 p.m.