Triple
T23514946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maggie Murdock |
E574332
|
entity |
| Predicate | relationshipTypeWithJamieRandall |
P152684
|
FINISHED |
| Object | on-and-off romantic relationship |
—
|
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: on-and-off romantic relationship | Statement: [Maggie Murdock, relationshipTypeWithJamieRandall, on-and-off romantic relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithJamieRandall Context triple: [Maggie Murdock, relationshipTypeWithJamieRandall, on-and-off romantic relationship]
-
A.
relationshipWithJamie
Indicates a relationship or connection that an entity has with Jamie.
-
B.
relationshipTypeWithJakeBarnes
Indicates the specific nature or category of relationship that an entity has with Jake Barnes.
-
C.
relationshipTypeWithHayleyTravis
Indicates the specific nature or category of the relationship that an entity has with Hayley Travis.
-
D.
relationshipTypeWithSamMalone
Indicates the specific nature or category of relationship that an entity has with Sam Malone.
-
E.
relationshipTypeWithRandy "The Ram" Robinson
Indicates the specific nature or category of relationship that an entity has with Randy "The Ram" Robinson.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa80d9048190ab735dddd301feb4 |
completed | April 29, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 6:08 p.m.