Triple
T24345878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States v. Lara |
E613636
|
entity |
| Predicate | modifiesEffectOf |
P125417
|
FINISHED |
| Object | Duro v. Reina |
—
|
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: Duro v. Reina | Statement: [United States v. Lara, modifiesEffectOf, Duro v. Reina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modifiesEffectOf Context triple: [United States v. Lara, modifiesEffectOf, Duro v. Reina]
-
A.
laterAmendedEffect
chosen
Indicates that one legal act or provision modifies or changes the effect of an earlier act or provision at a later point in time.
-
B.
conditionalEffect
Indicates that one event, state, or action occurs or holds only if a specified condition is met.
-
C.
providesEffect
Indicates that one entity causes, delivers, or produces a particular effect or outcome on another entity.
-
D.
ultimateEffect
Indicates the final or overall outcome that results from a preceding action, condition, or sequence of events.
-
E.
opposesEffectOf
Indicates that one entity counteracts, reduces, or nullifies the effect produced by another entity.
- 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_69e2d7ddd29481909e7f539a6072bd71 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2932978b88190afc441a3d4805e5f |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:58 a.m.