Triple
T16779231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvia |
E407812
|
entity |
| Predicate | relationshipToTruman |
P124598
|
FINISHED |
| Object | romantic interest |
—
|
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: romantic interest | Statement: [Sylvia, relationshipToTruman, romantic interest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToTruman Context triple: [Sylvia, relationshipToTruman, romantic interest]
-
A.
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.
-
B.
TrumanCharacterization
Indicates how the character of Truman is portrayed or described in terms of traits, behavior, or role.
-
C.
associatedPresident
Indicates a relationship where a person, organization, event, or entity is linked or connected to a specific president in a relevant or significant way.
-
D.
TrumanParty
Indicates the political party affiliation associated with Harry S. Truman.
-
E.
hasPresidentialConnection
Indicates that there exists a notable relationship, association, or link between an entity and a president or presidential office.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b21401b881909bbbc7382e851a90 |
completed | April 18, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326bac94481908c082117553320f8 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:22 a.m.