Triple
T17840457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meryl Burbank |
E445508
|
entity |
| Predicate | relationshipTypeWithTruman |
P124596
|
FINISHED |
| Object | arranged marriage |
—
|
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: arranged marriage | Statement: [Meryl Burbank, relationshipTypeWithTruman, arranged marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithTruman Context triple: [Meryl Burbank, relationshipTypeWithTruman, arranged marriage]
-
A.
relationshipToTruman
Indicates the specific familial, social, or professional connection that an entity has with Truman.
-
B.
relationshipToTrumanBurbank
chosen
Indicates the type or nature of a person's relationship to Truman Burbank.
-
C.
termRelationToPresident
Indicates the nature of a person’s connection or role in relation to a president, such as their position, association, or involvement with that president.
-
D.
TrumanCharacterization
Indicates how the character of Truman is portrayed or described in terms of traits, behavior, or role.
-
E.
relationshipTypeWithTaylorTravis
Indicates the specific nature or category of the relationship that an entity has with Taylor Travis.
- 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_69d8b9f1a6d881909f024bc603111cdb |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48d2b2ea08190926ec0cf01285833 |
completed | April 19, 2026, 8:07 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e266888190ae976b4b7d5b886f |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:16 a.m.