Triple
T31645234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabhi |
E807567
|
entity |
| Predicate | usesKakaliNishada |
P172047
|
FINISHED |
| Object | N3 |
—
|
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: N3 | Statement: [Arabhi, usesKakaliNishada, N3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesKakaliNishada Context triple: [Arabhi, usesKakaliNishada, N3]
-
A.
kokudaka
Indicates a relationship where a landholding or domain is assigned a value based on its assessed agricultural productivity or tax yield, typically measured in koku.
-
B.
hasDaishido
Indicates that an entity possesses, includes, or is associated with a Daishidō (a specific hall, building, or designated area).
-
C.
KaumodakiOf
Indicates that one entity is the Kaumodaki (the specific mace/weapon) associated with, possessed by, or emblematic of another entity.
-
D.
usesKatakanaFor
Indicates that one entity is written or represented using katakana script in relation to another entity.
-
E.
SakaeIs
Indicates that one entity is identified as or classified as "Sakae" in relation to another entity or context.
- 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_69f348d9ce58819093ea2da83cbeeec1 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a956e9b08190bf83547bba8e8147 |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a757c6e081908e37631e5d8d246b |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a8036ab481908019f2f071fa406e |
completed | May 3, 2026, 1:42 a.m. |
Created at: April 30, 2026, 10:50 p.m.