Triple
T32561851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1984 New York City subway shooting |
E832247
|
entity |
| Predicate | hasLegalCharge |
P194478
|
FINISHED |
| Object | attempted murder |
—
|
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: attempted murder | Statement: [1984 New York City subway shooting, hasLegalCharge, attempted murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalCharge Context triple: [1984 New York City subway shooting, hasLegalCharge, attempted murder]
-
A.
hasLegalIssue
Indicates that an entity is involved in, associated with, or subject to a legal problem, dispute, or proceeding.
-
B.
hasLegalRight
Indicates that an entity possesses an officially recognized legal entitlement or permission to perform an action or hold a claim regarding another entity.
-
C.
haveCriminalLaw
Indicates that an entity possesses, applies, or is governed by a system or body of criminal law.
-
D.
hasMainCharge
Indicates that one entity is the primary or principal charge, responsibility, or obligation associated with another entity.
-
E.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
- F. None of above. chosen
Provenance (4 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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd76d1e5208190a6f26651492d1e3c |
completed | May 8, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69fd702a226c81908edfda00f4be4130 |
completed | May 8, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69fd76d0d7608190b350336d6c18182d |
completed | May 8, 2026, 5:38 a.m. |
Created at: May 1, 2026, 1:03 a.m.