Triple
T299310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | chicken |
E6161
|
entity |
| Predicate | welfareConcern |
P10570
|
FINISHED |
| Object | battery cages |
—
|
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: battery cages | Statement: [chicken, welfareConcern, battery cages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: welfareConcern Context triple: [chicken, welfareConcern, battery cages]
-
A.
welfareModel
Indicates a relationship where a system, policy, or framework defines how welfare or social support is structured, delivered, and governed for its beneficiaries.
-
B.
welfareState
Indicates a relationship where a government assumes primary responsibility for ensuring citizens’ social and economic well-being through public services, income support, and social protection policies.
-
C.
concernsRight
Indicates that something is about or relates specifically to a legal or moral right held by an entity.
-
D.
aimsToProtect
Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
-
E.
policyFocus
Indicates that an entity (such as a person, organization, or document) is primarily concerned with, directed toward, or centered on a particular policy area or issue.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea0dd1dc8190aecd5afdeb2fd74b |
completed | Feb. 28, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69a2e9398df08190af40063a2de7a1d0 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea07e3bc8190bae593b3264de211 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.