Triple
T31978236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Will Traynor |
E816504
|
entity |
| Predicate | relationshipTypeWith Louisa Clark |
P206136
|
FINISHED |
| Object | 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: romantic relationship | Statement: [Will Traynor, relationshipTypeWith Louisa Clark, romantic relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Louisa Clark Context triple: [Will Traynor, relationshipTypeWith Louisa Clark, romantic relationship]
-
A.
relationshipToLucyHoneychurch
Indicates the specific type of relationship or connection an entity has to Lucy Honeychurch.
-
B.
relationshipTypeWithLorraineBroughton
Indicates the specific nature or category of relationship an entity has with Lorraine Broughton.
-
C.
relationshipToEleanorVance
Indicates the specific nature or type of relationship an entity has with Eleanor Vance.
-
D.
relationshipTypeWithMargaretSchlegel
Indicates the specific type or nature of the relationship that an entity has with Margaret Schlegel.
-
E.
relationshipTypeWithGwendolenFairfax
Indicates the specific nature or category of relationship that an entity has with Gwendolen Fairfax.
- 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_69f348f6a3008190bfb59ca695fd68e2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 12:11 a.m.