Triple
T18693014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zunka Bhakri |
E457045
|
entity |
| Predicate | zunkaOftenIncludes |
P1393
|
FINISHED |
| Object | tempered mustard seeds |
—
|
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: tempered mustard seeds | Statement: [Zunka Bhakri, zunkaOftenIncludes, tempered mustard seeds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zunkaOftenIncludes Context triple: [Zunka Bhakri, zunkaOftenIncludes, tempered mustard seeds]
-
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.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
C.
isEatenIn
Indicates that one entity (typically food) is consumed within the context, location, or occasion specified by another entity.
-
D.
isTypicallyConsumedFrom
Indicates that one entity is most commonly eaten or drunk using, contained in, or taken from the other entity.
-
E.
noodleType
Indicates the specific kind or category of noodle associated with an entity.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e562e4756881909335e1e7b3c23e28 |
completed | April 19, 2026, 11:19 p.m. |
| PD | Predicate disambiguation | batch_69e478de85088190ba5f005f1d39f587 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:49 a.m.