Triple
T23726680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harris Ranch |
E586294
|
entity |
| Predicate | hasOnsiteMeatProcessing |
P119617
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Harris Ranch, hasOnsiteMeatProcessing, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnsiteMeatProcessing Context triple: [Harris Ranch, hasOnsiteMeatProcessing, true]
-
A.
hasAbattoir
chosen
Indicates that one entity possesses, contains, or is the site of an abattoir (slaughterhouse) used for animal slaughter or meat processing.
-
B.
isProcessedFood
Indicates that a food item has been altered from its natural state through industrial or mechanical methods such as refining, adding ingredients, or preserving.
-
C.
notableMeatProduct
Indicates that one entity is a meat-based product that is especially prominent, well-known, or significant in relation to the other entity.
-
D.
meatPreparation
Indicates the method or process by which meat is treated, cooked, or otherwise prepared for consumption.
-
E.
meatContent
Indicates that one entity has a specified amount, proportion, or presence of meat contained within it.
- 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_69e24906fb108190a6898751e46bdc11 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b915a888819088e92f99711e8120 |
completed | April 29, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:08 p.m.