Triple
T23056762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Augie |
E574178
|
entity |
| Predicate | relationshipToJasmineFrench |
P150807
|
FINISHED |
| Object | ex-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: ex-husband | Statement: [Augie, relationshipToJasmineFrench, ex-husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToJasmineFrench Context triple: [Augie, relationshipToJasmineFrench, ex-husband]
-
A.
relationshipToMonsieurJourdain
Indicates the type or nature of a person’s relationship to Monsieur Jourdain.
-
B.
relationshipToParis
Indicates the specific type of connection or association an entity has with Paris.
-
C.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
-
D.
relationshipTypeWithJulie d’Étange
Indicates the specific nature or category of the relationship that an entity has with Julie d’Étange.
-
E.
nameInFrench
Indicates that an entity is known or referred to by a specific name expressed in the French 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_69e245ba7ae48190be606dbc54120e39 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1868099708190b23725dc8a305e09 |
completed | April 29, 2026, 4:18 a.m. |
| PD | Predicate disambiguation | batch_69ef89d5f71881908b9f9d0c8aab278c |
completed | April 27, 2026, 4:07 p.m. |
| PDg | Predicate description generation | batch_69ef9b7494f4819088ae59ea3d0ae8ab |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 3:55 p.m.