Triple
T9264559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mama |
E222662
|
entity |
| Predicate | supportsOrganizationGoal |
P39887
|
FINISHED |
| Object | reconnecting America via the chiral network |
—
|
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: reconnecting America via the chiral network | Statement: [Mama, supportsOrganizationGoal, reconnecting America via the chiral network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsOrganizationGoal Context triple: [Mama, supportsOrganizationGoal, reconnecting America via the chiral network]
-
A.
supportGoal
chosen
Indicates that one entity actively helps, promotes, or contributes to the achievement of another entity’s goal.
-
B.
supportsOrganization
Indicates that one entity provides assistance, resources, or advocacy that helps sustain or advance an organization.
-
C.
supportsPolicyGoal
Indicates that one entity’s actions, positions, or characteristics help advance, uphold, or contribute to achieving a specified policy goal.
-
D.
supportsGoalType
Indicates that one entity is compatible with, or designed to facilitate, a particular type or category of goal.
-
E.
supportsOrganizationUseCase
Indicates that one entity provides the necessary functionality or conditions for an organization to carry out a specific use case or operational scenario.
- 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_69ca841f2e808190a64f4c31903a1332 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0748a1f481909d9d876692cefccc |
completed | April 1, 2026, 11:53 a.m. |
| PD | Predicate disambiguation | batch_69cc7a537bbc8190baee71f556e52a7b |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:32 p.m.