Triple
T28567130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cinnamon |
E722710
|
entity |
| Predicate | sometimesSeenWith |
P22648
|
FINISHED |
| Object | Bernadette Rostenkowski-Wolowitz |
—
|
NE NERFINISHED |
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: Bernadette Rostenkowski-Wolowitz | Statement: [Cinnamon, sometimesSeenWith, Bernadette Rostenkowski-Wolowitz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sometimesSeenWith Context triple: [Cinnamon, sometimesSeenWith, Bernadette Rostenkowski-Wolowitz]
-
A.
canBeSeenWith
chosen
Indicates that two entities are observable together in the same context, setting, or time.
-
B.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
C.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
-
D.
notablyUsedWith
Indicates that one entity is commonly or prominently used together with another entity, in a way that is especially characteristic or noteworthy.
-
E.
alsoUsedIn
Indicates that something is additionally employed, applied, or present in another context, setting, or use case beyond the primary one.
- F. None of above.
Provenance (3 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_69f01a5f69d08190ad5c0d2167078dec |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6508f9be0819094d2968611578175 |
completed | May 2, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 4:07 a.m.