Triple
T21506486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Report on the Meat-Packing Industry |
E530609
|
entity |
| Predicate | identifiesProblem |
P15680
|
FINISHED |
| Object | threats to consumer health |
—
|
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: threats to consumer health | Statement: [Report on the Meat-Packing Industry, identifiesProblem, threats to consumer health]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: identifiesProblem Context triple: [Report on the Meat-Packing Industry, identifiesProblem, threats to consumer health]
-
A.
typicalProblem
Indicates that a situation, issue, or obstacle is representative or characteristic of the usual problems encountered in a given context.
-
B.
problemType
Indicates the specific category or classification of a problem within a defined problem space or system.
-
C.
helpsIdentify
Indicates a relationship where one entity serves to distinguish, recognize, or determine the identity or characteristics of another entity.
-
D.
problemStatement
chosen
Indicates that an entity presents, defines, or expresses a specific problem or issue to be addressed.
-
E.
problems
Indicates that one entity has issues, difficulties, or complications associated with or caused by another entity.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea7d8be881908ff8a58b8a6eff40 |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e631f6e68081908f5ee4ce7413803e |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:24 p.m.