Triple
T23842114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quahog Cemetery |
E591015
|
entity |
| Predicate | hasNotableBurialFictional |
P3803
|
FINISHED |
| Object | Francis Griffin |
—
|
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: Francis Griffin | Statement: [Quahog Cemetery, hasNotableBurialFictional, Francis Griffin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableBurialFictional Context triple: [Quahog Cemetery, hasNotableBurialFictional, Francis Griffin]
-
A.
hasFictionalCemetery
Indicates that an entity includes, features, or is associated with a cemetery that is fictional rather than real.
-
B.
hasNotableBurials
chosen
Indicates that a place, typically a cemetery or burial site, contains the graves or remains of individuals considered notable or significant.
-
C.
hasFictionalFuneralDirectors
Indicates that an entity includes or features fictional characters who serve as funeral directors.
-
D.
buriedInFiction
Indicates that one entity is depicted as being buried within a fictional work, narrative, or story world rather than in real life.
-
E.
hasBurialsOf
Indicates that a location or site contains or includes the burial places of certain individuals or groups.
- 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_69e25d1de32c8190a907afe9c3d6cd6d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c888c13c8190b85d2cd425ee84dc |
completed | April 29, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:09 p.m.