Triple
T20688596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nadine Boca |
E508488
|
entity |
| Predicate | hasRoleInRelationships |
P161
|
FINISHED |
| Object | story’s relationships revolve around her |
—
|
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: story’s relationships revolve around her | Statement: [Nadine Boca, hasRoleInRelationships, story’s relationships revolve around her]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoleInRelationships Context triple: [Nadine Boca, hasRoleInRelationships, story’s relationships revolve around her]
-
A.
hasRelativeRole
Indicates that one entity holds a familial or kinship-based role in relation to another entity.
-
B.
hasRole
chosen
Indicates that an entity occupies, performs, or is assigned a specific role or function in relation to another entity or context.
-
C.
includesRoles
Indicates that one entity contains or encompasses one or more specified roles within its scope or structure.
-
D.
hasRelationships
Indicates that an entity is connected to one or more other entities through specified types of relationships.
-
E.
hasRoleInNetwork
Indicates that an entity holds a specific functional position or responsibility within a particular network.
- 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_69e0b4c1ed408190b72dd26b1e33f8a1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c10b7b808190bdb8b08e53168fb8 |
completed | April 21, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69e5c03caee881908be4dd25796a03d5 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:49 a.m.