Triple
T37129769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patrick Warburton as Agamemnon |
E919484
|
entity |
| Predicate | usesTimeTravelDevice |
P79914
|
FINISHED |
| Object | WABAC machine |
—
|
NE NERFINISHED |
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: WABAC machine | Statement: [Patrick Warburton as Agamemnon, usesTimeTravelDevice, WABAC machine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTimeTravelDevice Context triple: [Patrick Warburton as Agamemnon, usesTimeTravelDevice, WABAC machine]
-
A.
timeTravelDeviceUsed
chosen
Indicates that an entity makes use of a device or mechanism that enables travel through time.
-
B.
usesTimeTravelFor
Indicates a relationship where an entity employs time travel as a means or method to achieve, affect, or interact with another entity or objective.
-
C.
timeTravelCapability
Indicates the ability of an entity to travel between different points in time.
-
D.
timeTravelInvolvement
Indicates that an entity participates in, is affected by, or is otherwise involved in an instance of time travel.
-
E.
hasTemporalParadox
Indicates that a situation, event, or sequence of events involves a contradiction or inconsistency in time, such as conflicting timelines or causality loops.
- 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_69f76e9d13e48190a108f7fbf80ff375 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: May 3, 2026, 4:15 p.m.