Triple
T30307582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hasekura Tsunenaga |
E770826
|
entity |
| Predicate | presentedLettersTo |
P182765
|
FINISHED |
| Object | Pope Paul V |
—
|
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: Pope Paul V | Statement: [Hasekura Tsunenaga, presentedLettersTo, Pope Paul V]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: presentedLettersTo Context triple: [Hasekura Tsunenaga, presentedLettersTo, Pope Paul V]
-
A.
hasLettersFor
Indicates that one entity possesses or contains written correspondence intended for another entity.
-
B.
openingLetters
Indicates that one entity is the initial or first letter(s) of another entity (such as a word, name, or string).
-
C.
settingOfManyLetters
Indicates a setting or context in which many letters (such as written messages or characters) occur, are exchanged, or are central to the situation.
-
D.
hasLetterBy
Indicates that an entity possesses or is associated with a letter authored or sent by another entity.
-
E.
representedTo
Indicates that one entity formally acted on behalf of or served as the representative of another entity in a given context or interaction.
- F. None of above. chosen
Provenance (4 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_69f22488f224819081b0f3ec41ab975c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7908ec35881909a42f954fb9fa16e |
completed | May 3, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69f78fd3fd888190b7db0b563f298585 |
completed | May 3, 2026, 6:11 p.m. |
Created at: April 29, 2026, 7:49 p.m.