Triple
T20667378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macon Leary |
E507927
|
entity |
| Predicate | relationshipToMurielPritchett |
P140986
|
FINISHED |
| Object | boyfriend |
—
|
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: boyfriend | Statement: [Macon Leary, relationshipToMurielPritchett, boyfriend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMurielPritchett Context triple: [Macon Leary, relationshipToMurielPritchett, boyfriend]
-
A.
relationshipToHollyGolightly
Indicates the nature or type of relationship an entity has with Holly Golightly.
-
B.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
-
C.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
D.
relationshipToGeorgeAndMartha
Indicates the specific familial, social, or other relational connection that an entity has to the pair George and Martha considered together.
-
E.
relationshipToElaineBenes
Indicates a person's specific relational connection (such as friend, partner, or family member) to Elaine Benes.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5c4c4608190ae17da4a59e5ae80 |
completed | April 20, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3caef50819093c8159fe8d6435b |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 11:44 a.m.