Triple
T1622532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yokohama F. Marinos |
E35063
|
entity |
| Predicate | formedByMergerInYear |
P176
|
FINISHED |
| Object | 1999 |
—
|
LITERAL 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: 1999 | Statement: [Yokohama F. Marinos, formedByMergerInYear, 1999]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formedByMergerInYear Context triple: [Yokohama F. Marinos, formedByMergerInYear, 1999]
-
A.
mergerYear
chosen
Indicates the year in which two or more entities formally merged into a single entity.
-
B.
foundedByMergerOf
Indicates that an entity was created through the merger or combination of two or more predecessor entities.
-
C.
dissolvedByMerger
Indicates that an entity ceased to exist as an independent entity because it was legally combined into another entity through a merger.
-
D.
mergerPartner
Indicates that two entities are involved as counterparties in a merger transaction with each other.
-
E.
wasUnifiedWith
Indicates that two or more previously separate entities were brought together to form a single unified whole.
- 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_69a886023194819080a3fccd6e325d0e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf4a0ef748190ae52b9656474c0ef |
completed | March 6, 2026, 3:37 p.m. |
| PD | Predicate disambiguation | batch_69a907c731808190a1d998155041b3c1 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.