Triple
T35513857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humberto Munoz-Flores |
E1026357
|
entity |
| Predicate | caseHeWasIn_fullCaseName |
P3131
|
FINISHED |
| Object | United States v. Munoz-Flores |
—
|
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: United States v. Munoz-Flores | Statement: [Humberto Munoz-Flores, caseHeWasIn_fullCaseName, United States v. Munoz-Flores]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseHeWasIn_fullCaseName Context triple: [Humberto Munoz-Flores, caseHeWasIn_fullCaseName, United States v. Munoz-Flores]
-
A.
fullCaseName
chosen
Indicates that one entity is the complete, formal name of a legal case associated with another entity.
-
B.
caseHeWasIn_citation
Indicates that a citation is associated with, or refers to, a legal case that he was involved in.
-
C.
caseHeBrought
Indicates that a male subject initiated and brought a legal case or lawsuit against another party.
-
D.
accusedName
Indicates that a particular person or entity is identified as the one who is accused in an accusation or legal charge.
-
E.
namesakeFullName
Indicates that one entity’s full name is used as the namesake or source of the name for 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_69f76dfd61208190b93ec6dc439cab41 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:04 p.m.