Triple
T35094510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marquise de San-Réal |
E1012829
|
entity |
| Predicate | relationshipTypeWithHenriDeMarsay |
P206836
|
FINISHED |
| Object | rival in love |
—
|
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: rival in love | Statement: [Marquise de San-Réal, relationshipTypeWithHenriDeMarsay, rival in love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithHenriDeMarsay Context triple: [Marquise de San-Réal, relationshipTypeWithHenriDeMarsay, rival in love]
-
A.
relationshipToMarquisDeLantenac
Indicates a familial or social connection that a person or entity has with the Marquis de Lantenac.
-
B.
relationshipToMariane
Indicates the specific type of relationship or connection that an entity has to Mariane.
-
C.
relationshipTypeWithManonLescaut
Indicates the specific nature or category of relationship that an entity has with Manon Lescaut.
-
D.
relationshipToEdmondDantès
Indicates the specific type of personal or social relationship an entity has with Edmond Dantès.
-
E.
relationshipTypeWithMarnie
Indicates the specific nature or category of relationship that an entity has with Marnie.
- 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_69f76dd432ec8190969bc32acfc152b1 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:01 p.m.