Triple
T14778232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nadine Franklin |
E347318
|
entity |
| Predicate | relationshipStatusWithKrista |
P115751
|
FINISHED |
| Object | best friends since childhood |
—
|
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: best friends since childhood | Statement: [Nadine Franklin, relationshipStatusWithKrista, best friends since childhood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithKrista Context triple: [Nadine Franklin, relationshipStatusWithKrista, best friends since childhood]
-
A.
relationshipStatusWithMichael
Indicates the type or state of the relationship that an entity currently has with Michael.
-
B.
relationshipStatusWithBrian
Indicates the current nature or state of an entity’s personal relationship with Brian.
-
C.
relationshipToJoannaKramer
Indicates the specific familial, social, or interpersonal connection that one entity has to Joanna Kramer.
-
D.
relationshipStatusInStory
Indicates the type or state of the relationship between entities as it exists within the context of a specific story or narrative.
-
E.
relationshipTypeWithStephanie Ramzinski
Indicates the specific nature or category of relationship that an entity has with Stephanie Ramzinski.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec817c39081909b08a0ffdfce9936 |
completed | April 14, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69de8c02e5c08190943c27594026faf7 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:31 a.m.