Triple
T22593208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melton Mowbray pork pie |
E565002
|
entity |
| Predicate | hasFillingCharacteristic |
P148860
|
FINISHED |
| Object | coarsely chopped pork |
—
|
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: coarsely chopped pork | Statement: [Melton Mowbray pork pie, hasFillingCharacteristic, coarsely chopped pork]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFillingCharacteristic Context triple: [Melton Mowbray pork pie, hasFillingCharacteristic, coarsely chopped pork]
-
A.
hasFillingType
Indicates that an entity is associated with a specific type or category of filling it contains or uses.
-
B.
hasFillingFactor
Indicates that one entity is associated with a specific filling factor value characterizing how fully a space, volume, or capacity is occupied.
-
C.
hasFillingSystem
Indicates that an entity is equipped with or uses a particular filling system or mechanism.
-
D.
isTypicallyFilledWith
Indicates that one entity is commonly or usually occupied, loaded, or contained by another entity.
-
E.
isFilledPastry
Indicates that one item is a pastry whose interior is filled with another substance, such as cream, fruit, or other fillings.
- 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f16163cb248190b377b110d80a6730 |
completed | April 29, 2026, 1:39 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
| PDg | Predicate description generation | batch_69ee8841e9cc81908d23b34215e3be71 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 2:49 p.m.