Triple
T3357623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess of Japan |
E70642
|
entity |
| Predicate | titleInJapaneseScript |
P4863
|
FINISHED |
| Object | 内親王 or 女王 (depending on lineage and law) |
—
|
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: 内親王 or 女王 (depending on lineage and law) | Statement: [Princess of Japan, titleInJapaneseScript, 内親王 or 女王 (depending on lineage and law)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleInJapaneseScript Context triple: [Princess of Japan, titleInJapaneseScript, 内親王 or 女王 (depending on lineage and law)]
-
A.
titleInJapanese
chosen
Indicates that one entity is the title of another entity expressed specifically in the Japanese language.
-
B.
titleInHebrew
Indicates that an entity has a specific title expressed in the Hebrew language.
-
C.
titleInVietnamese
Indicates that one entity is the title of another entity expressed in the Vietnamese language.
-
D.
titleInEnglish
Indicates that an entity’s title or name is given in the English language.
-
E.
titleInRussian
Indicates that an entity’s title is given or recorded in the Russian language.
- 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_69ad85a660c48190998489309a3b4869 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb244435c81908e35d2aa36ec4f46 |
completed | March 8, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69ada42fbe7c8190b9f185b5ab985f17 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.