Triple
T10642210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron de Wolmar |
E250749
|
entity |
| Predicate | relationshipToJulie |
P95126
|
FINISHED |
| Object | protector |
—
|
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: protector | Statement: [Baron de Wolmar, relationshipToJulie, protector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToJulie Context triple: [Baron de Wolmar, relationshipToJulie, protector]
-
A.
relationshipToRelative
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
B.
relationshipToLaurie
Indicates the specific type of relationship or connection that an entity has to Laurie.
-
C.
relationshipToHannah
Indicates the specific type of relationship or connection that an entity has to Hannah.
-
D.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
-
E.
relationshipToMother
Indicates the specific familial or social connection an entity has to its mother.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfce1ddc8190893fe6f7b047b56b |
completed | April 8, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69d6dd83b114819098e84dc658e82d7e |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df463ea8819091d6683e476b4f21 |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 9:05 p.m.