Triple
T2005478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | March of Dimes |
E43570
|
entity |
| Predicate | formerFocus |
P35083
|
FINISHED |
| Object | polio |
—
|
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: polio | Statement: [March of Dimes, formerFocus, polio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerFocus Context triple: [March of Dimes, formerFocus, polio]
-
A.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
C.
focusesBy
Indicates that one entity directs its attention, effort, or emphasis toward another entity or specific aspect of it.
-
D.
formerSurface
Indicates that one entity previously served as the surface or outer layer of another entity, but no longer does so.
-
E.
formerGround
Indicates that an entity previously served as the ground or base for another entity but no longer holds that role.
- 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_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb898795481909920c1a4c4d62c2d |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb79e63c08190982c8b44a557266f |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb87b9fc08190a748c278ef2d7dc7 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:37 p.m.