Triple
T23663644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pontefract cake |
E584516
|
entity |
| Predicate | isTypicallyBlackDueTo |
P152905
|
FINISHED |
| Object | concentrated liquorice extract |
—
|
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: concentrated liquorice extract | Statement: [Pontefract cake, isTypicallyBlackDueTo, concentrated liquorice extract]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTypicallyBlackDueTo Context triple: [Pontefract cake, isTypicallyBlackDueTo, concentrated liquorice extract]
-
A.
hasAllBlack
Indicates that the subject possesses or consists entirely of things that are black in color.
-
B.
hasFleshColor
Indicates that an entity possesses a particular color or characteristic of its flesh or internal tissue.
-
C.
blackPrajiadIn
Indicates that an entity possesses or is wearing a black prajiad (armband) within a given context or location.
-
D.
hasFacialSkinColor
Indicates that one entity has a specific facial skin color characterized or attributed by another entity.
-
E.
hasEthnicCharacteristic
Indicates that an entity possesses or is associated with a particular ethnic characteristic or identity.
- 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_69e248ffc0888190ae23c4731eb8b7ac |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b40a1284819087cd29c9c390549d |
completed | April 29, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f121cc494081908c987adfcde89b0e |
completed | April 28, 2026, 9:08 p.m. |
Created at: April 17, 2026, 6:50 p.m.