Triple
T680745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carl Denham |
E13174
|
entity |
| Predicate | plotInvolvement |
P17462
|
FINISHED |
| Object | faces lawsuits after King Kong's rampage |
—
|
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: faces lawsuits after King Kong's rampage | Statement: [Carl Denham, plotInvolvement, faces lawsuits after King Kong's rampage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plotInvolvement Context triple: [Carl Denham, plotInvolvement, faces lawsuits after King Kong's rampage]
-
A.
involvedActor
Indicates that an entity participates as an actor or participant in the referenced event, activity, or situation.
-
B.
playedKeyRoleIn
Indicates that an entity had a major, influential, or decisive impact on the occurrence, outcome, or success of another entity or event.
-
C.
notableProgramInvolvement
Indicates that an entity has a significant or distinguished role or participation in a particular program.
-
D.
playerInvolved
Indicates that a specific player participates in, is associated with, or takes part in a particular event, action, or situation.
-
E.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
- 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_69a4933d3bf88190972041cd8cf143b9 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a06e294c8190873116a3253e04f9 |
completed | March 1, 2026, 8:24 p.m. |
| PD | Predicate disambiguation | batch_69a49d1d79608190a849ba9ffad2879d |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a49df19c9481909cc9bc33ed7f011b |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.