Triple
T5292794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loves Music, Loves to Dance |
E119779
|
entity |
| Predicate | hasCrimeType |
P7957
|
FINISHED |
| Object | serial 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: serial murder | Statement: [Loves Music, Loves to Dance, hasCrimeType, serial murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrimeType Context triple: [Loves Music, Loves to Dance, hasCrimeType, serial murder]
-
A.
haveCriminalLaw
Indicates that an entity possesses, applies, or is governed by a system or body of criminal law.
-
B.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
C.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or entity.
-
D.
convictedOf
Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal process.
-
E.
consideredCriminalBy
Indicates that one party regards or classifies another party as a criminal according to its own laws, rules, or judgments.
- 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_69bd446f22b88190b6a47fb91c68a3e7 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8682d18c8190bbb35cc75c8a7c12 |
completed | March 20, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69bd844dfdac819086efedd1cbebff84 |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:52 p.m.