Triple
T37578524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cortes |
E934889
|
entity |
| Predicate | thirdEstateRepresentation |
P31178
|
FINISHED |
| Object | town representatives |
—
|
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: town representatives | Statement: [Cortes, thirdEstateRepresentation, town representatives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thirdEstateRepresentation Context triple: [Cortes, thirdEstateRepresentation, town representatives]
-
A.
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.
-
B.
sectorRepresented
chosen
Indicates that an entity serves as a representative or proxy for a particular sector (such as an industry, domain, or market segment).
-
C.
principalFrenchRepresentative
Indicates that one entity serves as the primary official representative of France in relation to another entity.
-
D.
numberOfDeputiesSecondEstate
Indicates the total count of deputies or representatives belonging to the Second Estate in a given context.
-
E.
eraRepresented
Indicates that a subject depicts, symbolizes, or stands for a particular historical or temporal era.
- 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_69f76ecd99148190be327e391a70f5b6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd4f39b5008190b83b3227ce22c509 |
completed | May 8, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69fd4df17c548190a4e2a6fea70f7e10 |
completed | May 8, 2026, 2:44 a.m. |
Created at: May 3, 2026, 4:17 p.m.