Triple
T7665355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Composite |
E173610
|
entity |
| Predicate | CompositeNodeRole |
P78652
|
FINISHED |
| Object | represents objects that have children |
—
|
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: represents objects that have children | Statement: [Composite, CompositeNodeRole, represents objects that have children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CompositeNodeRole Context triple: [Composite, CompositeNodeRole, represents objects that have children]
-
A.
canonicalRole
Indicates that an entity holds a standard, primary, or officially recognized role within a particular context or system.
-
B.
configurationRole
Indicates the role or function an entity assumes within a particular configuration or setup.
-
C.
roleWithCEP
Indicates that an entity holds a specific role or function that is associated with a defined Contextualized Event or Process (CEP).
-
D.
CDCRole
Indicates that one entity holds a specific role or function within a clinical data collection (CDC) context relative to another entity.
-
E.
sonRole
Indicates that one entity holds the role or relationship of a son with respect to 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7063dab1881909598b04999b8b690 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015f7430819099d3ea2781b7cee2 |
completed | March 27, 2026, 10:14 p.m. |
| PDg | Predicate description generation | batch_69c7063cfd78819095c6501fe8d57312 |
completed | March 27, 2026, 10:35 p.m. |
Created at: March 27, 2026, 4 p.m.