Triple
T9939545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Celia Coplestone |
E194042
|
entity |
| Predicate | deathLocationInFiction |
P21
|
FINISHED |
| Object | remote mission in Kinkanja |
—
|
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: remote mission in Kinkanja | Statement: [Celia Coplestone, deathLocationInFiction, remote mission in Kinkanja]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathLocationInFiction Context triple: [Celia Coplestone, deathLocationInFiction, remote mission in Kinkanja]
-
A.
traditionalPlaceOfDeath
Indicates the location where a person is customarily or culturally considered to have died, according to traditional or historical accounts.
-
B.
deathInFiction
Indicates that an entity’s death occurs within a fictional work or narrative rather than in real life.
-
C.
placeOfDeath
chosen
Indicates the location where an entity (typically a person or animal) died.
-
D.
bodyLocationAfterDeath
Indicates the location or position of an entity’s body after its death.
-
E.
deathTypeInFiction
Indicates the manner or category of how a character dies within a fictional narrative.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e819e08190967b799fd236749e |
completed | April 2, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9428cc81909b4b4938566d78a7 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:44 p.m.