Triple
T30946886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dark Tower (novel) |
E788416
|
entity |
| Predicate | containsCharacterDeath |
P51826
|
FINISHED |
| Object | Eddie Dean |
—
|
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: Eddie Dean | Statement: [The Dark Tower (novel), containsCharacterDeath, Eddie Dean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsCharacterDeath Context triple: [The Dark Tower (novel), containsCharacterDeath, Eddie Dean]
-
A.
containsDeathOf
chosen
Indicates that the subject includes, depicts, or involves the death of the referenced entity.
-
B.
hasMurderVictimCharacter
Indicates that an entity (such as a work of fiction or event) includes or involves a character who is the victim of a murder.
-
C.
hasDiedInSeries
Indicates that an entity has died at some point within the narrative of a particular series.
-
D.
hasDifferentFateOfCharacter
Indicates that two characters experience distinct outcomes or destinies within a narrative or scenario.
-
E.
legendaryDeath
Indicates a death that is renowned or celebrated in stories or history, often marked by extraordinary circumstances or lasting fame.
- 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_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff49016dcc8190a8a43868c728b4f1 |
completed | May 9, 2026, 2:47 p.m. |
| PD | Predicate disambiguation | batch_69ff4891924c8190b5be340e2520e012 |
completed | May 9, 2026, 2:45 p.m. |
Created at: April 29, 2026, 8:53 p.m.