Triple
T9034799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anakin Skywalker |
E216463
|
entity |
| Predicate | turnsTo |
P28004
|
FINISHED |
| Object | dark side of the Force |
—
|
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: dark side of the Force | Statement: [Anakin Skywalker, turnsTo, dark side of the Force]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnsTo Context triple: [Anakin Skywalker, turnsTo, dark side of the Force]
-
A.
turnsIn
Indicates that an entity submits or hands over something, typically work or an item, to another party or authority.
-
B.
turns
chosen
Indicates a change in orientation, direction, or state initiated by one entity affecting itself or another entity.
-
C.
numberOfTurns
Indicates the total count of discrete turns or rotations involved in an interaction, process, or motion.
-
D.
turningPointIn
Indicates that an event or situation serves as a decisive change or pivotal moment within a larger process, narrative, or development.
-
E.
turnout
Indicates the number or proportion of participants who attend or take part in an event or activity.
- 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_69ca83d10b608190b2b2f8e0a7faaf14 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6abf4af481908d21245332329d99 |
completed | April 1, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee3597c81908919cf866ae95c24 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:08 p.m.