Triple
T13008387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcie |
E322344
|
entity |
| Predicate | relationshipToPeppermintPatty |
P107802
|
FINISHED |
| Object | friend and classmate |
—
|
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: friend and classmate | Statement: [Marcie, relationshipToPeppermintPatty, friend and classmate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToPeppermintPatty Context triple: [Marcie, relationshipToPeppermintPatty, friend and classmate]
-
A.
relationshipToKittyBennet
Indicates the specific type of personal or familial connection an entity has to Kitty Bennet.
-
B.
relationshipToPatsey
Indicates the nature or type of relationship an entity has with the person or entity named Patsey.
-
C.
relationshipToBenjy
Indicates the specific type of relationship or connection an entity has to Benjy.
-
D.
relationshipToHenry
Indicates the specific type of relationship or connection that an entity has to Henry.
-
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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e9cf0108190b02f498c6ccc91f8 |
completed | April 10, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69d97dc153a081909d13a694993f074a |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97e74283c819082e69ac3554fa7d8 |
completed | April 10, 2026, 10:49 p.m. |
Created at: April 9, 2026, 8:48 p.m.