Triple
T3163439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | aloo paratha |
E66153
|
entity |
| Predicate | usesFat |
P4791
|
FINISHED |
| Object | ghee |
—
|
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: ghee | Statement: [aloo paratha, usesFat, ghee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesFat Context triple: [aloo paratha, usesFat, ghee]
-
A.
usedOnFront
Indicates that something is applied, displayed, or positioned on the front side or front-facing part of another object or entity.
-
B.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
C.
usedWith
chosen
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
D.
usedCross
Indicates that one entity made use of a cross-shaped object or structure, or traversed by means of a crossing point such as a crosswalk or intersection.
-
E.
usesFrequency
Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
- 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_69ad85850c1481908a9e9c6242238de2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada61a4b8481908897a8d39d94c2f4 |
completed | March 8, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9dfe0a948190928f2201d671c654 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:06 p.m.