Triple
T16329337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agnieszka |
E396506
|
entity |
| Predicate | cognate |
P2527
|
FINISHED |
| Object | Inés |
E398718
|
NE 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: Inés | Statement: [Agnieszka, cognate, Inés]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inés Context triple: [Agnieszka, cognate, Inés]
-
A.
Inés
chosen
Inés is a feminine given name, especially common in Spanish-speaking countries, derived from the name Agnes.
-
B.
Pilar
Pilar is a Spanish royal, known formally as Infanta Pilar, Duchess of Badajoz, and a member of the House of Bourbon.
-
C.
Pilar
Pilar is the introspective female protagonist of Paulo Coelho’s novel "By the River Piedra I Sat Down and Wept," whose spiritual and emotional journey drives the story.
-
D.
Pilar
Pilar is a coastal town on Siargao Island in the Philippines, known for its fishing communities and access to popular surfing and eco-tourism spots.
-
E.
Pilar
Pilar is a Spanish feminine given name, often associated with religious devotion to Our Lady of the Pillar and traditionally used in Spain and Spanish-speaking countries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4ddc5608190b24fe2e871691470 |
completed | April 17, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002da915ac8190820acbe0db72c8a1 |
completed | May 10, 2026, 7:03 a.m. |
Created at: April 10, 2026, 5:07 a.m.