Triple
T34767882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Grand |
E1002269
|
entity |
| Predicate | relationshipTypeWith Bernard Rieux |
P205546
|
FINISHED |
| Object | friend |
—
|
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: friend | Statement: [Joseph Grand, relationshipTypeWith Bernard Rieux, friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Bernard Rieux Context triple: [Joseph Grand, relationshipTypeWith Bernard Rieux, friend]
-
A.
relationshipToBernardBlack
Indicates the specific nature of an entity’s relationship or connection to Bernard Black.
-
B.
relationshipToBobinot
Indicates the nature or type of relationship that one entity has with Bobinot.
-
C.
relationshipToThérèse Raquin
Indicates the specific type of relationship or connection an entity has to Thérèse Raquin.
-
D.
relationshipToBéralde
Indicates the type or nature of a person or entity’s relationship to Béralde.
-
E.
relationshipToEdmondDantès
Indicates the specific type of personal or social relationship an entity has with Edmond Dantès.
- 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_69f76db20dac8190b1e8d0ca4dc1d59f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 3:59 p.m.