Triple
T13255042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Hubbell |
E315634
|
entity |
| Predicate | relationshipTypeWithEunice |
P109170
|
FINISHED |
| Object | married couple with frequent quarrels |
—
|
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: married couple with frequent quarrels | Statement: [Steve Hubbell, relationshipTypeWithEunice, married couple with frequent quarrels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithEunice Context triple: [Steve Hubbell, relationshipTypeWithEunice, married couple with frequent quarrels]
-
A.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
B.
relationshipToSophie
Indicates the specific type of personal or social connection that an entity has to Sophie.
-
C.
relationshipToOdette
Indicates the specific familial, social, or interpersonal connection that an entity has with Odette.
-
D.
relationshipTypeWithJulie d’Étange
Indicates the specific nature or category of the relationship that an entity has with Julie d’Étange.
-
E.
relationshipToJulie
Indicates a specified type of relationship or connection that an entity has to Julie.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f60911081909fa346a054f76c9f |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99cf7f9c48190a6a4f452b4a2aefa |
completed | April 11, 2026, 12:59 a.m. |
Created at: April 9, 2026, 9:24 p.m.