Triple
T20415780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gremio |
E500707
|
entity |
| Predicate | relationshipToBianca |
P140053
|
FINISHED |
| Object | unsuccessful suitor |
—
|
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: unsuccessful suitor | Statement: [Gremio, relationshipToBianca, unsuccessful suitor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToBianca Context triple: [Gremio, relationshipToBianca, unsuccessful suitor]
-
A.
relationshipToCarmen
Indicates the specific type of personal or social relationship an entity has with Carmen.
-
B.
relationshipToJuana
Indicates a specified type of relationship or connection that an entity has to Juana.
-
C.
relationshipToJohanna
Indicates the specific type of relationship or connection that an entity has with Johanna.
-
D.
relationshipToVanessa
Indicates the specific type of personal or social relationship that an entity has with Vanessa.
-
E.
relationshipWithMarcello
Indicates that there exists some form of relationship or connection between an entity and Marcello.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a437eec8190a20c89a236dd5bc0 |
completed | April 20, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69e5766df0008190a73c4f613c29678f |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:30 a.m.