Triple
T20012550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gratiano |
E494623
|
entity |
| Predicate | relationshipToNerissa |
P138373
|
FINISHED |
| Object | husband |
—
|
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: husband | Statement: [Gratiano, relationshipToNerissa, husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToNerissa Context triple: [Gratiano, relationshipToNerissa, husband]
-
A.
relationshipToTess
Indicates the specific type of relationship or connection that an entity has to Tess.
-
B.
relationshipToJohanna
Indicates the specific type of relationship or connection that an entity has with Johanna.
-
C.
relationshipToTristan
Indicates the specific type of personal, social, or familial connection that one entity has with the individual named Tristan.
-
D.
relationshipToNicole
Indicates the specific type of relationship or connection that an entity has with Nicole.
-
E.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66238f434819083b11458179bb601 |
completed | April 20, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69e54cdddbd48190becc8b2aa5ab4ef9 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:34 p.m.