Triple
T8669509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jango Fett |
E205758
|
entity |
| Predicate | employedTo |
P83995
|
FINISHED |
| Object | assassinate Padmé Amidala |
—
|
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: assassinate Padmé Amidala | Statement: [Jango Fett, employedTo, assassinate Padmé Amidala]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employedTo Context triple: [Jango Fett, employedTo, assassinate Padmé Amidala]
-
A.
employedApproximately
Indicates that one entity employs another in a manner where the number, duration, or extent of employment is approximate rather than exact.
-
B.
employedSystem
Indicates that a system is used or operated in the context of an employment or work-related arrangement.
-
C.
employedRole
Indicates that an entity holds or performs a specific role or position within an employment or work context.
-
D.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
-
E.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
- 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4917cb9881909a73b74e54250613 |
completed | March 31, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc46c330bc8190a9b644078881c6ff |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:31 p.m.