Triple
T3505542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marchioness |
E74065
|
entity |
| Predicate | equivalentTitleInPortuguese |
P48374
|
FINISHED |
| Object | Marquesa |
—
|
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: Marquesa | Statement: [Marchioness, equivalentTitleInPortuguese, Marquesa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentTitleInPortuguese Context triple: [Marchioness, equivalentTitleInPortuguese, Marquesa]
-
A.
equivalentTitleInFrench
Indicates that one entity’s title is the equivalent or corresponding title of another entity, specifically expressed in French.
-
B.
equivalentOrRelatedTitle
Indicates that two titles are the same or sufficiently similar in meaning, role, or status to be treated as equivalent or closely related.
-
C.
analogousTitle
Indicates that one entity has a title or position that corresponds in role, rank, or function to the title or position held by another entity.
-
D.
equivalentTitleInEngland
Indicates that one title corresponds to an equivalent or matching title within the context of England’s system of titles.
-
E.
nameInPortuguese
Indicates that an entity is referred to by a specific name when expressed in the Portuguese language.
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbf38e988190998d722b95830411 |
completed | March 8, 2026, 6:12 p.m. |
| PD | Predicate disambiguation | batch_69adae0e770481908528fa35eda53003 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaed74ecc8190b74dc70ab59a3e1c |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:18 p.m.