Triple
T38283353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zissou Society |
E1022134
|
entity |
| Predicate | targetOfInterest |
P860
|
FINISHED |
| Object | fans of The Life Aquatic with Steve Zissou |
—
|
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: fans of The Life Aquatic with Steve Zissou | Statement: [Zissou Society, targetOfInterest, fans of The Life Aquatic with Steve Zissou]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetOfInterest Context triple: [Zissou Society, targetOfInterest, fans of The Life Aquatic with Steve Zissou]
-
A.
target
chosen
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
B.
targetsUseCase
Indicates that one entity is aimed at or designed to address a particular use case associated with another entity.
-
C.
targetsVector
Indicates that one entity is directed toward, aimed at, or focused on another entity represented as a vector (e.g., a direction or target position).
-
D.
targetOfIntervention
Indicates that an entity is the object or focus upon which an intervention, treatment, or action is directed.
-
E.
targetConcern
Indicates that something is the specific issue, problem, or subject that is the focus of attention, action, or consideration.
- 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_69f76df0cddc81908d16c1556ff4097f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff59b33a38819086cc9aa19b81748b |
completed | May 9, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69ff587758f88190a39c2164341dc554 |
completed | May 9, 2026, 3:53 p.m. |
Created at: May 3, 2026, 4:30 p.m.