Triple
T37107353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cammareri Brothers Bakery |
E918880
|
entity |
| Predicate | associatedWithCharacterFamilyName |
P125063
|
FINISHED |
| Object | Cammareri |
E918881
|
NE 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: Cammareri | Statement: [Cammareri Brothers Bakery, associatedWithCharacterFamilyName, Cammareri]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCharacterFamilyName Context triple: [Cammareri Brothers Bakery, associatedWithCharacterFamilyName, Cammareri]
-
A.
associatedWithCharacterFamily
chosen
Indicates a relationship where something is linked or connected to a particular character’s family.
-
B.
associatedWithCharacterAlias
Indicates that one entity is linked to or connected with an alternative name or alias used for a particular character.
-
C.
associatedWithCharacterGroup
Indicates that an entity has a connection or affiliation with a particular group of characters.
-
D.
associatedWithCharacterRole
Indicates that one entity has a connection or linkage to a specific character role played or held by another entity.
-
E.
associatedWithFilmCharacterType
Indicates that an entity has an association or connection with a particular type or category of film character.
- F. None of above.
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_69f76e9b99c8819096164b21ff5bd996 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3efdd9b70481908a7d5a07059bcd22 |
completed | June 26, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:14 p.m.