Triple
T29150574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheriff Graham Humbert |
E738895
|
entity |
| Predicate | statusInStorybrooke |
P193305
|
FINISHED |
| Object | deceased |
—
|
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: deceased | Statement: [Sheriff Graham Humbert, statusInStorybrooke, deceased]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusInStorybrooke Context triple: [Sheriff Graham Humbert, statusInStorybrooke, deceased]
-
A.
narrativeStatus
Indicates the role or state of an element within a narrative, such as whether it is current, hypothetical, background, or otherwise positioned in the story’s progression.
-
B.
storyWorldStatus
Indicates the current state or condition of the fictional world in which a story’s events take place.
-
C.
storyStatus
Indicates the current state or phase of a story within its lifecycle (e.g., planned, in progress, completed, or archived).
-
D.
townStatus
Indicates the administrative or legal status of a settlement as a town (e.g., whether and how it is officially recognized or classified as a town).
-
E.
statusInComicSeries
Indicates the role or condition a character or entity holds within the context of a specific comic series (e.g., main, supporting, deceased, cameo).
- 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_69f07cb46f148190874eb8576a447567 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
| PDg | Predicate description generation | batch_69fd4128ed908190837ec9936774a1cf |
completed | May 8, 2026, 1:49 a.m. |
Created at: April 28, 2026, 11:42 a.m.