Triple
T9593601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premier Grand Cru Classé A |
E231476
|
entity |
| Predicate | expandedNumberOfEstatesBy2012 |
P34583
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Premier Grand Cru Classé A, expandedNumberOfEstatesBy2012, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: expandedNumberOfEstatesBy2012 Context triple: [Premier Grand Cru Classé A, expandedNumberOfEstatesBy2012, 4]
-
A.
numberOfEstates
Indicates the total count of estates associated with a given entity or context.
-
B.
numberOfClassifiedEstates
chosen
Indicates the count of estates that have been formally classified or categorized in a given context.
-
C.
numberOfDeputiesFirstEstate
Indicates the quantity of deputies or representatives associated with the First Estate in a given context.
-
D.
hadEstate
Indicates that an entity possessed or owned a particular estate or landed property.
-
E.
representedEstate
Indicates that one party has acted as a legal or official representative for a particular estate in matters such as administration, management, or proceedings.
- 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_69ca8482884481908eccdfdf64d6fbf7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a134b0c81908a568e5d2ecfbb92 |
completed | April 1, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a359788190b24f82399489f7fe |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:07 p.m.