Triple
T31045297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hara Kei |
E791107
|
entity |
| Predicate | precededBy (Prime Minister of Japan) |
P4358
|
FINISHED |
| Object | Terauchi Masatake |
—
|
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: Terauchi Masatake | Statement: [Hara Kei, precededBy (Prime Minister of Japan), Terauchi Masatake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: precededBy (Prime Minister of Japan) Context triple: [Hara Kei, precededBy (Prime Minister of Japan), Terauchi Masatake]
-
A.
precededBy (as Prime Minister)
Indicates that one person previously held the office of Prime Minister before another person.
-
B.
precededBy (President of Italy)
Indicates that one President of Italy held office immediately before another President of Italy.
-
C.
precededByAsAmbassadorToJapan
Indicates that one entity previously served as ambassador to Japan before another entity did.
-
D.
predecessorAsPrimeMinister
chosen
Indicates that one person previously held the office of Prime Minister immediately before another person.
-
E.
predecessorAsFirstMinister
Indicates that one person previously held the position of First Minister immediately before another person.
- 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_69f224ca2fa881908a3ac5fedf207b90 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7a225a77c81908f8953ccfeb14336 |
completed | May 3, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
Created at: April 29, 2026, 8:59 p.m.