Triple
T22676000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life-in-Death |
E560345
|
entity |
| Predicate | relationToAncientMariner |
P149200
|
FINISHED |
| Object | tormentor |
—
|
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: tormentor | Statement: [Life-in-Death, relationToAncientMariner, tormentor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToAncientMariner Context triple: [Life-in-Death, relationToAncientMariner, tormentor]
-
A.
relationshipToMariner
Indicates the specific familial, social, or professional connection that an entity has to a mariner.
-
B.
relationToBenitoCereno
Indicates the specific relationship or connection an entity has to the character or figure Benito Cereno.
-
C.
relationshipToAhab
Indicates the specific type of personal or social connection an entity has with Ahab.
-
D.
relationshipWithProspero
Indicates that one entity has a specified type of interpersonal or narrative relationship with Prospero.
-
E.
relationToOdysseus
Indicates the specific familial, social, or narrative relationship that one entity has to Odysseus.
- F. None of above. chosen
Provenance (4 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1785ca1e08190af1a6cdb51ca4fce |
completed | April 29, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
| PDg | Predicate description generation | batch_69ee8843d3308190b6e22bb98ae5c3d8 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 3:11 p.m.