Triple
T34999905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flood on the Floss |
E1009644
|
entity |
| Predicate | causesDeathOfCharacter |
P54491
|
FINISHED |
| Object | Maggie Tulliver |
—
|
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: Maggie Tulliver | Statement: [Flood on the Floss, causesDeathOfCharacter, Maggie Tulliver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causesDeathOfCharacter Context triple: [Flood on the Floss, causesDeathOfCharacter, Maggie Tulliver]
-
A.
deathLeadsTo
Indicates that one entity’s death causes, results in, or brings about another event, state, or condition.
-
B.
deathBy
chosen
Indicates a relationship where one entity’s death is caused by another entity, event, or factor.
-
C.
effectOfDeath
Indicates the causal impact or consequences that a death has on another entity, state, or process.
-
D.
oneIndividualDies
Indicates that exactly one individual in a given context or group undergoes death.
-
E.
victimDiedIn
Indicates that the victim lost their life as a result of, or during the course of, the referenced event or circumstance.
- 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_69f76dcb716881909f75e4fd60ab2284 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: May 3, 2026, 4:01 p.m.