Triple
T38481567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin Clinton |
E915689
|
entity |
| Predicate | specialAbilityEffect |
P109271
|
FINISHED |
| Object | slows down time while driving |
—
|
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: slows down time while driving | Statement: [Franklin Clinton, specialAbilityEffect, slows down time while driving]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: specialAbilityEffect Context triple: [Franklin Clinton, specialAbilityEffect, slows down time while driving]
-
A.
heroPowerEffect
Indicates the specific impact or outcome that a hero’s power has when it is used.
-
B.
featuresSpecialAbility
chosen
Indicates that an entity possesses or is characterized by a particular special ability.
-
C.
specialEffectsBy
Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or entity.
-
D.
notableEffect
Indicates that one entity has a significant impact, consequence, or influence on another entity or situation.
-
E.
ultimateEffect
Indicates the final or overall outcome that results from a preceding action, condition, or sequence of events.
- 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_69f76e8ff5cc8190a88803369183845e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd6dbd1b648190b1a0b391c03aebc5 |
completed | May 8, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69fd6a9020548190bbfa845360ac85fb |
completed | May 8, 2026, 4:46 a.m. |
Created at: May 3, 2026, 4:31 p.m.