Triple
T27669923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yokohama F. Marinos |
E697630
|
entity |
| Predicate | FMeaning |
P66017
|
FINISHED |
| Object | Flügels (symbolic reference to former Yokohama Flügels) |
—
|
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: Flügels (symbolic reference to former Yokohama Flügels) | Statement: [Yokohama F. Marinos, FMeaning, Flügels (symbolic reference to former Yokohama Flügels)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FMeaning Context triple: [Yokohama F. Marinos, FMeaning, Flügels (symbolic reference to former Yokohama Flügels)]
-
A.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
B.
textMeaning
Indicates that one text expresses, conveys, or corresponds to a particular meaning or semantic content.
-
C.
apMeaning
chosen
Indicates that one entity expresses, conveys, or signifies the meaning or semantic content of another entity.
-
D.
commonMeaning
Indicates that multiple entities share the same or very similar meaning or semantic interpretation.
-
E.
duMeaning
Indicates that one entity expresses, conveys, or signifies a particular meaning or sense in relation to another.
- F. None of above.
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_69ef590d458c81909583290c3cd0478b |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f634a807c88190bb549a04e16bfd8d |
completed | May 2, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69f62c1a92648190835a2c5250d8c758 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:40 p.m.