Triple
T2075193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Daughter of the United States |
E44904
|
entity |
| Predicate | mayEngageIn |
P34786
|
FINISHED |
| Object | advocacy for social causes |
—
|
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: advocacy for social causes | Statement: [First Daughter of the United States, mayEngageIn, advocacy for social causes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayEngageIn Context triple: [First Daughter of the United States, mayEngageIn, advocacy for social causes]
-
A.
mayConduct
Indicates that one entity is permitted or authorized to carry out, perform, or execute a particular action, process, or operation on or with another entity.
-
B.
mayEnter
Indicates that one entity is permitted or authorized to enter or access another entity or location.
-
C.
mayMeet
Indicates that one entity is permitted or has the possibility to meet or come together with another entity.
-
D.
engagedBy
Indicates that an entity is actively involved, occupied, or participating in an activity, process, or interaction initiated or provided by another entity.
-
E.
mayBeChallengedBy
Indicates that one entity is allowed or able to be opposed, questioned, or contested by another entity.
- 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_69a88916c2b48190a5ca2e9b12cad3ed |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba116ea0819086d16c3913159e9e |
completed | March 7, 2026, 5:39 a.m. |
| PD | Predicate disambiguation | batch_69abb7b0edac8190a58eabee55f73deb |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb85fe7a08190b991b1f23bc34f93 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:41 p.m.