Triple
T25116698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kōgō |
E629145
|
entity |
| Predicate | predecessorTitleHolderExample |
P6041
|
FINISHED |
| Object | Empress Michiko |
—
|
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: Empress Michiko | Statement: [Kōgō, predecessorTitleHolderExample, Empress Michiko]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predecessorTitleHolderExample Context triple: [Kōgō, predecessorTitleHolderExample, Empress Michiko]
-
A.
predecessorTitleHolder
chosen
Indicates that one entity previously held a particular title or position before another entity.
-
B.
predecessorTitleContext
Indicates that the relationship specifies the contextual circumstances (such as role, period, or setting) under which a predecessor’s title is relevant or applies.
-
C.
successorTitleContext
Indicates the contextual circumstances or framework under which one title succeeds another.
-
D.
successorTitlesComparedWith
Indicates that the titles of successor entities are being compared to determine their relative similarity, difference, or ordering.
-
E.
successorTitleForHolders
Indicates that one title is the official successor title that replaces or follows the titles previously held by certain holders.
- 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_69e2ff3169d08190973b6061d5009abd |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 18, 2026, 6:27 a.m.