Triple
T35469830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evil League of Evil |
E1025175
|
entity |
| Predicate | targetOfCharacter |
P87321
|
FINISHED |
| Object | Dr. Horrible's ambition |
—
|
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: Dr. Horrible's ambition | Statement: [Evil League of Evil, targetOfCharacter, Dr. Horrible's ambition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetOfCharacter Context triple: [Evil League of Evil, targetOfCharacter, Dr. Horrible's ambition]
-
A.
targetsCharacter
chosen
Indicates that one entity is the intended focus or target of another entity’s action, effect, or behavior.
-
B.
targetOfAntagonists
Indicates that the referenced entity is the object or focus of hostile actions, opposition, or conflict initiated by antagonistic parties.
-
C.
targetInFiction
Indicates that one entity is the target or subject of an action, focus, or effect within a fictional work or narrative context.
-
D.
pursuingCharacter
Indicates that one character is actively chasing, seeking, or attempting to catch or reach another character.
-
E.
plotCharacter
Indicates a relationship where a character plays a role or participates in the narrative plot of a story or work.
- 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_69f76dfa20d0819089585dc2cf653aea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fedec693b08190b0f8bfdb921e0766 |
completed | May 9, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69fede16c1d48190a20d8a9c5722c307 |
completed | May 9, 2026, 7:11 a.m. |
Created at: May 3, 2026, 4:04 p.m.