Triple
T9257622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank James |
E222484
|
entity |
| Predicate | postCrimeActivity |
P87829
|
FINISHED |
| Object | worked as a lecturer |
—
|
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: worked as a lecturer | Statement: [Frank James, postCrimeActivity, worked as a lecturer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postCrimeActivity Context triple: [Frank James, postCrimeActivity, worked as a lecturer]
-
A.
regionOfCrimes
Indicates the geographic area or jurisdiction in which the crimes occurred or are attributed to an entity.
-
B.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
C.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
D.
crimeLocation
Indicates that a crime occurred at, or is associated with, a particular location.
-
E.
coversUpCrimeOf
Indicates that one entity conceals, protects, or hides the criminal actions or offenses committed by another entity.
- 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_69ca841e4cd481908e738c74e958eaea |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd06b660448190b6bc04beff0f5512 |
completed | April 1, 2026, 11:51 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4e79e48190b3200247f4624867 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc95597be081908ece2491dd2f0f74 |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:32 p.m.