Triple
T29884313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dagonet (2004 film character) |
E758966
|
entity |
| Predicate | sacrificesHimselfTo |
P113058
|
FINISHED |
| Object | save his comrades |
—
|
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: save his comrades | Statement: [Dagonet (2004 film character), sacrificesHimselfTo, save his comrades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sacrificesHimselfTo Context triple: [Dagonet (2004 film character), sacrificesHimselfTo, save his comrades]
-
A.
sacrificedBy
Indicates that an entity has been given up, killed, or offered as a sacrifice by another entity.
-
B.
sacrifice
Indicates giving up something of value, often for the benefit, protection, or advantage of another entity or goal.
-
C.
sacrificedLifeToSaveOthers
chosen
Indicates that an entity willingly gave up their own life in order to protect or rescue other entities.
-
D.
sacrificedTo
Indicates that one entity is offered or given up as a sacrifice in honor of, or to appease, another entity.
-
E.
sacrificeType
Indicates the specific kind or category of sacrifice involved in a sacrificial action or relationship.
- 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_69f2245de2f48190a481404896b56254 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f676fc2748819094f7048111b2b407 |
completed | May 2, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 5:59 p.m.