Triple
T34488358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | pastirma |
E885394
|
entity |
| Predicate | coatingIngredient |
P179415
|
FINISHED |
| Object | fenugreek |
—
|
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: fenugreek | Statement: [pastirma, coatingIngredient, fenugreek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coatingIngredient Context triple: [pastirma, coatingIngredient, fenugreek]
-
A.
coatingType
Indicates the type or kind of coating applied to or associated with an entity.
-
B.
coatingFunction
Indicates that one entity serves as a coating or covering layer that provides a specific protective or functional effect to another entity.
-
C.
ingredientType
Indicates that one entity is classified as a specific type or category of ingredient in relation to another.
-
D.
containsAdditives
Indicates that one entity includes or is composed of additional substances or ingredients beyond its primary or original components.
-
E.
coFormulatedWith
Indicates that one entity is formulated together with another as part of the same combined product or composition.
- 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_69f349c947fc81909d30b53c194d6ea1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f720cc1bfc8190a16118e3af8e9316 |
completed | May 3, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
| PDg | Predicate description generation | batch_69f71fb0172c81908f23e95ff16b0dec |
completed | May 3, 2026, 10:13 a.m. |
Created at: May 1, 2026, 2:01 a.m.