Triple
T7416267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maeda clan |
E171137
|
entity |
| Predicate | income |
P76820
|
FINISHED |
| Object | over one million koku |
—
|
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: over one million koku | Statement: [Maeda clan, income, over one million koku]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: income Context triple: [Maeda clan, income, over one million koku]
-
A.
incomeType
Indicates the category or source classification of an entity’s income within a given context.
-
B.
salary
Indicates the amount of monetary compensation an entity receives, typically on a regular basis, for work or services performed.
-
C.
incomeTreatment
Indicates a relationship where an entity receives, is subject to, or is affected by a particular income-related treatment, policy, or classification.
-
D.
incomeMeasure
Indicates a relationship where one entity serves as a measure or metric of another entity’s income.
-
E.
incomeCounted
Indicates that a specified amount of income is included in a particular calculation, assessment, or determination (such as eligibility, benefits, or totals).
- 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2c7ae0c8190a8348d6223aeeecc |
completed | March 27, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1c3307481909a7f6bb69d4fddac |
completed | March 27, 2026, 9:08 p.m. |
Created at: March 27, 2026, 3:11 p.m.