Triple
T4357876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferdinand Walsin Esterhazy |
E98593
|
entity |
| Predicate | wroteDocument |
P2831
|
FINISHED |
| Object | bordereau |
—
|
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: bordereau | Statement: [Ferdinand Walsin Esterhazy, wroteDocument, bordereau]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wroteDocument Context triple: [Ferdinand Walsin Esterhazy, wroteDocument, bordereau]
-
A.
documentedBy
Indicates that something is recorded, described, or evidenced in a specific document or set of documents.
-
B.
wroteIn
Indicates that an entity authored or composed something using a particular language, medium, or writing system.
-
C.
wrote
chosen
Indicates that an entity is the author or creator of a written work involving another entity.
-
D.
writtenDuring
Indicates that the creation or authorship of something took place within a specified time period or historical event.
-
E.
hasWrittenFor
Indicates that one entity has created written content (such as articles, stories, or texts) for or on behalf of another entity, typically a publication, organization, or platform.
- F. None of above.
Provenance (3 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_69b3454c772081908e20173e379e8ebe |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351c7fa1881908bdc844a7142eb65 |
completed | March 12, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69b34f51ed7c8190b7bf5f44b56b730d |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:16 p.m.