Triple
T21140960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince N. |
E520923
|
entity |
| Predicate | relationshipToTatyanaLarina |
P143015
|
FINISHED |
| Object | husband |
—
|
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: husband | Statement: [Prince N., relationshipToTatyanaLarina, husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToTatyanaLarina Context triple: [Prince N., relationshipToTatyanaLarina, husband]
-
A.
relationshipToPierreBezukhov
Indicates the specific type of personal or social relationship an entity has to Pierre Bezukhov.
-
B.
relationshipToOnegin
Indicates the specific interpersonal or familial relationship that one entity has to the person named Onegin.
-
C.
relationshipToPrinceNikolaiBolkonsky
Indicates the specific familial, social, or interpersonal relationship that an entity has to Prince Nikolai Bolkonsky.
-
D.
relationshipToPavelVlasov
Indicates the nature or type of relationship an entity has with Pavel Vlasov.
-
E.
relationshipTypeWithTaniaFedorova
Indicates the specific nature or category of relationship that an entity has with Tania Fedorova.
- 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_69e0b50c6a848190a4e525a77a319b8a |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7235f77708190809d6aa3ee8056aa |
completed | April 21, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e5f5ed6c8c8190b31092a5d4c3de5d |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5f993240c8190847c0b08e65726c8 |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 2:57 p.m.