Triple
T20769580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carol Bridger |
E511188
|
entity |
| Predicate | hasStatusInStory |
P35677
|
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: [Carol Bridger, hasStatusInStory, deceased]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStatusInStory Context triple: [Carol Bridger, hasStatusInStory, deceased]
-
A.
teamStatusInStory
Indicates the status or role a team holds within the context of a particular story or narrative.
-
B.
storyStatus
Indicates the current state or phase of a story within its lifecycle (e.g., planned, in progress, completed, or archived).
-
C.
narrativeStatus
chosen
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.
-
D.
hasStaffTypeInStory
Indicates that a story involves or is associated with a particular type or category of staff.
-
E.
isStoried
Indicates that something has a rich history, reputation, or legacy built up over time, often marked by notable events or traditions.
- 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_69e0b4ca01148190ac018e57e0cab46f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c265f7dc8190a084e35d38d2783a |
completed | April 21, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c0550ec481908a0877fb2409d983 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:36 p.m.