Triple
T1915554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iris Steensma |
E40008
|
entity |
| Predicate | relationshipTypeWithTravisBickle |
P10690
|
FINISHED |
| Object | rescued by |
—
|
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: rescued by | Statement: [Iris Steensma, relationshipTypeWithTravisBickle, rescued by]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithTravisBickle Context triple: [Iris Steensma, relationshipTypeWithTravisBickle, rescued by]
-
A.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
portraysRelationship
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
-
C.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
D.
hasFamilialTieTo
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
-
E.
hasProtagonistRelationship
Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1e517e8819086e4bf5a305aeb25 |
completed | March 7, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69abafed2ab481908920334e77b1021b |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.