Triple
T6418666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diego Forlán |
E127890
|
entity |
| Predicate | playedForClub |
P2168
|
FINISHED |
| Object | Cerezo Osaka |
E578449
|
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: Cerezo Osaka | Statement: [Diego Forlán, playedForClub, Cerezo Osaka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cerezo Osaka Context triple: [Diego Forlán, playedForClub, Cerezo Osaka]
-
A.
Cerezo Osaka
chosen
Cerezo Osaka is a professional Japanese football club based in Osaka, known for competing in the J1 League and for its intense local rivalry with Gamba Osaka in the Osaka derby.
-
B.
Kashiwa
Kashiwa is a city in Chiba Prefecture, Japan, known as a residential and commercial hub within the Greater Tokyo metropolitan area.
-
C.
Osakasayama
Osakasayama is a suburban city in Osaka Prefecture, Japan, known for its residential character and proximity to the Osaka metropolitan area.
-
D.
Kichijōji
Kichijōji is a popular Tokyo neighborhood known for its trendy shopping streets, vibrant dining and nightlife, and the expansive Inokashira Park.
-
E.
Ōsu
Ōsu is a popular shopping and entertainment district in Nagoya, Japan, known for its mix of traditional temples, vintage shops, electronics stores, and street food.
- 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_69c0083815208190a9b299b8e0640218 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c068eb6c988190b54de6182d0f490d |
completed | March 22, 2026, 10:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640d2ab64819089e91525da60392b |
completed | March 27, 2026, 8:33 a.m. |
Created at: March 22, 2026, 4:42 p.m.