Triple
T26634611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaucouleurs |
E668600
|
entity |
| Predicate | JoanOfArcMet |
P161595
|
FINISHED |
| Object | Robert de Baudricourt |
—
|
NE NERFINISHED |
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: Robert de Baudricourt | Statement: [Vaucouleurs, JoanOfArcMet, Robert de Baudricourt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: JoanOfArcMet Context triple: [Vaucouleurs, JoanOfArcMet, Robert de Baudricourt]
-
A.
notableFemaleHero
Indicates that the subject is a female individual recognized for heroic actions or qualities that make her notably distinguished.
-
B.
historicalHeir
Indicates that one entity is recognized as the successor or inheritor of another in a historical or dynastic context.
-
C.
historicalFigure
Indicates that an entity is recognized as a notable person from the past who played a significant role in history.
-
D.
eraDepicted
Indicates that a work or representation portrays, illustrates, or is set in a particular historical era or time period.
-
E.
basedOnHistoricalFigure
Indicates that something is derived from, inspired by, or modeled after a real historical person.
- 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_69ee9d0024b8819090a7c8cf669a3b6c |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f61ad613608190855de13501a86007 |
completed | May 2, 2026, 3:40 p.m. |
| PD | Predicate disambiguation | batch_69f611ab768c8190b1849c15a3e59dda |
completed | May 2, 2026, 3 p.m. |
| PDg | Predicate description generation | batch_69f61a16b7848190bf20d2be7e5a16c1 |
completed | May 2, 2026, 3:36 p.m. |
Created at: April 27, 2026, 2:26 a.m.