Triple
T17327926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosamond Vivian |
E420734
|
entity |
| Predicate | relationshipTypeWithPhilipTempest |
P127022
|
FINISHED |
| Object | obsessive |
—
|
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: obsessive | Statement: [Rosamond Vivian, relationshipTypeWithPhilipTempest, obsessive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithPhilipTempest Context triple: [Rosamond Vivian, relationshipTypeWithPhilipTempest, obsessive]
-
A.
relationshipToPhilipMarlow
Indicates the specific type of personal or social relationship an entity has to Philip Marlow.
-
B.
hasRelationshipTypeWith Tai Frasier
Indicates that there exists a specific type of relationship between an entity and Tai Frasier.
-
C.
relationTypeToHenryVIII
Indicates the specific type of relationship an entity has to Henry VIII (e.g., familial, political, or social connection).
-
D.
hasPoliticalRelationshipWith
Indicates a political connection or association between two entities, such as alliances, rivalries, collaborations, or other forms of political interaction.
-
E.
relationshipTypeWithElizabethLeefolt
Indicates the specific nature or category of relationship an entity has with Elizabeth Leefolt.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439d42154819093a240f677a63145 |
completed | April 19, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69e3b021a5bc81909ae55406f9d0b37f |
completed | April 18, 2026, 4:24 p.m. |
| PDg | Predicate description generation | batch_69e3b2a225b08190a50f984caa6513b9 |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:43 a.m.