Triple
T30293129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William C. Hammer |
E770434
|
entity |
| Predicate | hasNameInCourtRecords |
P191016
|
FINISHED |
| Object | Dagenhart |
—
|
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: Dagenhart | Statement: [William C. Hammer, hasNameInCourtRecords, Dagenhart]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameInCourtRecords Context triple: [William C. Hammer, hasNameInCourtRecords, Dagenhart]
-
A.
appearsInPublicRecordsIn
chosen
Indicates that an entity is documented or mentioned in public records associated with a particular place or jurisdiction.
-
B.
namedForCourt
Indicates that one entity bears a name that was given or designated by a court or judicial authority.
-
C.
criminalRecord
Indicates that an entity has a documented history of criminal offenses or convictions recorded by an authority.
-
D.
associatedWithCrimeRecordOfUser
Indicates a relationship where something is linked to, or derived from, the crime record belonging to a specific user.
-
E.
hasLegalPrecedentName
Indicates that a legal case, decision, or precedent is associated with a specific formal name or citation title.
- 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_69f224875c288190a9b96b975006ec4a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdb04ed81c8190b8feea90c1c785a6 |
completed | May 8, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69fda9d6c5148190a63205b6d9b0a1b4 |
completed | May 8, 2026, 9:16 a.m. |
Created at: April 29, 2026, 7:47 p.m.