Triple
T16944737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Palladino |
E411038
|
entity |
| Predicate | roleInGilmoreGirls |
P83930
|
FINISHED |
| Object | writer |
—
|
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: writer | Statement: [Daniel Palladino, roleInGilmoreGirls, writer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInGilmoreGirls Context triple: [Daniel Palladino, roleInGilmoreGirls, writer]
-
A.
relativeTypeToHappyGilmore
Indicates that one entity is a specific type of relative or family relation to the entity Happy Gilmore.
-
B.
familyOrganizerRole
Indicates the specific role or capacity an individual holds as the organizer or manager within a family group or household.
-
C.
portrayedFamilyMemberOf
Indicates that one entity has depicted another entity as a member of their family, typically in a creative or representational context such as art, film, or literature.
-
D.
narrativeRoleInSeries
chosen
Indicates the specific narrative function or role an entity plays within a particular series or serialized work.
-
E.
spouseOccupationInSeries
Indicates that a character’s spouse has a particular occupation within the context of a series.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cfb14b788190be5b7f9c00c3e7ea |
completed | April 18, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b9aa8748190b248890aca86753d |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:31 a.m.