Triple
T5652838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All Around the Town |
E124544
|
entity |
| Predicate | involvesCrime |
P7957
|
FINISHED |
| Object | 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: murder | Statement: [All Around the Town, involvesCrime, murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesCrime Context triple: [All Around the Town, involvesCrime, murder]
-
A.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
B.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or entity.
-
C.
recognitionOfCrimes
Indicates the formal acknowledgment or identification that certain actions or events constitute crimes under a legal or normative framework.
-
D.
crimeListedInArticleIII
Indicates that a particular crime is one of the offenses expressly mentioned in Article III of the relevant constitution or legal document.
-
E.
constantInvolved
Indicates that a constant participates in or is directly involved in the specified relation, operation, or context.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d8a2588190b10de59edbc8841f |
completed | March 22, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69c01b2274b48190b2ef57ed728f785c |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:42 p.m.