Triple
T7166902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gwendoline Mary Lacey |
E167091
|
entity |
| Predicate | relationshipTypeWith Darrell Rivers |
P38921
|
FINISHED |
| Object | classmate |
—
|
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: classmate | Statement: [Gwendoline Mary Lacey, relationshipTypeWith Darrell Rivers, classmate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Darrell Rivers Context triple: [Gwendoline Mary Lacey, relationshipTypeWith Darrell Rivers, classmate]
-
A.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
B.
relatedTeam
Indicates that two teams are connected or associated with each other in a relevant or meaningful way.
-
C.
playerRelations
Indicates the nature or status of the relationship between players, such as alliances, rivalries, or other interpersonal dynamics.
-
D.
relationshipToNFL
Indicates the nature or type of connection an entity has to the National Football League (NFL), such as affiliation, role, or involvement.
-
E.
relationshipToCharacter
chosen
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e85a07388190a07054ef12870fa1 |
completed | March 27, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69c6e1cd5c948190a9113b23f7308c21 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:48 p.m.