Triple
T31348467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landrum |
E799515
|
entity |
| Predicate | hasNotableAssociatedLaw |
P142158
|
FINISHED |
| Object | Landrum–Griffin Act |
—
|
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: Landrum–Griffin Act | Statement: [Landrum, hasNotableAssociatedLaw, Landrum–Griffin Act]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableAssociatedLaw Context triple: [Landrum, hasNotableAssociatedLaw, Landrum–Griffin Act]
-
A.
hasRelationshipToLaw
chosen
Indicates that one entity has a defined connection, relevance, or applicability to a specific law or legal framework.
-
B.
hasLegalRelevanceIn
Indicates that something is legally significant, applicable, or has consequences within a specified legal context, case, or jurisdiction.
-
C.
hasNotableCaseDescribed
Indicates that a subject has a specific notable case or example that is explicitly described or documented.
-
D.
notableLegalCode
Indicates that a legal code is especially significant, influential, or noteworthy in relation to the referenced entity.
-
E.
containsLaw
Indicates that one entity (such as a document, code, or jurisdiction) includes or encompasses a specific law within it.
- 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_69f224e51614819083141459a080e97c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a009a0e1fa481909ed881012009b268 |
completed | May 10, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_6a0092e9fcb08190a966d720684f25ec |
completed | May 10, 2026, 2:15 p.m. |
Created at: April 29, 2026, 9:17 p.m.