Triple
T862303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Baby Food Action Network |
E18623
|
entity |
| Predicate | hasAreaOfActivity |
P19746
|
FINISHED |
| Object | public 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: public health | Statement: [International Baby Food Action Network, hasAreaOfActivity, public health]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAreaOfActivity Context triple: [International Baby Food Action Network, hasAreaOfActivity, public health]
-
A.
hasActivityIn
chosen
Indicates that an entity engages in or performs a particular activity within a specified context, location, or domain.
-
B.
hasEconomicActivity
Indicates that an entity engages in, supports, or is associated with a specific type of economic activity or business operation.
-
C.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
D.
historicallyActiveIn
Indicates that an entity was active or engaged in significant activities within a particular place or context during a past historical period.
-
E.
hasResearchArea
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac67d4d481909487d3edb3e46936 |
completed | March 1, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69a4aa84835081908aaf98b10656d7d6 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.