Triple
T20426705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suzanne Beckett |
E501019
|
entity |
| Predicate | relationshipToSamuelBeckett |
P140091
|
FINISHED |
| Object | longtime partner |
—
|
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: longtime partner | Statement: [Suzanne Beckett, relationshipToSamuelBeckett, longtime partner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToSamuelBeckett Context triple: [Suzanne Beckett, relationshipToSamuelBeckett, longtime partner]
-
A.
relationshipToSamuelJones
Indicates a specified type of relationship or connection that an entity has to Samuel Jones.
-
B.
relationshipToLeopoldBloom
Indicates the specific type of personal or social relationship an entity has with Leopold Bloom.
-
C.
relationshipToGustav von Aschenbach
Indicates the specific type of personal, social, or emotional connection an entity has to Gustav von Aschenbach.
-
D.
relationshipTypeWithRobertCohn
Indicates the specific nature or category of relationship that an entity has with Robert Cohn.
-
E.
relationshipToSamCarmichael
Indicates the specific type of personal or social relationship an entity has with Sam Carmichael.
- 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_69e0b4aa68fc8190b1a14c55575ef04a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67ba9700481909fa23493f98095d1 |
completed | April 20, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69e5766df0008190a73c4f613c29678f |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:30 a.m.