Triple
T11318266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cosmo Castorini |
E268020
|
entity |
| Predicate | relationshipToRose Castorini |
P98486
|
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: [Cosmo Castorini, relationshipToRose Castorini, husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToRose Castorini Context triple: [Cosmo Castorini, relationshipToRose Castorini, husband]
-
A.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
B.
relationshipTypeWith Francesca Johnson
Indicates the specific nature or category of the relationship that an entity has with Francesca Johnson.
-
C.
relationshipTypeWithRobertAngier
Indicates the specific nature or category of relationship that an entity has with Robert Angier.
-
D.
relationshipToAligoté
Indicates the specific type of relationship or connection an entity has to Aligoté (typically a wine grape or wine style).
-
E.
relationshipToCatherine
Indicates the specific familial, social, or interpersonal connection that one entity has to the person named Catherine.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c3cf748190987838029d9f7fff |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787ad575081908274280bf75d95fd |
completed | April 9, 2026, 11:04 a.m. |
| PDg | Predicate description generation | batch_69d796d049e88190a9fd7508f477f541 |
completed | April 9, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:32 p.m.