Triple
T5366472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angela Vicario |
E103143
|
entity |
| Predicate | timeOfLetters |
P1936
|
FINISHED |
| Object | many years after the 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: many years after the murder | Statement: [Angela Vicario, timeOfLetters, many years after the murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfLetters Context triple: [Angela Vicario, timeOfLetters, many years after the murder]
-
A.
timeToSentence
Indicates the amount of time that elapses from a relevant starting point (e.g., offense, arrest, or charge) until a formal sentence is imposed.
-
B.
timeDescribedAs
Indicates that a specific time or temporal interval is characterized, labeled, or expressed using a particular description or representation.
-
C.
timeNotation
Indicates the specific system or format used to represent and write times (e.g., 12-hour vs 24-hour notation).
-
D.
timeStructure
Indicates that one entity defines, constrains, or organizes the temporal framework or schedule within which another entity exists or operates.
-
E.
time
chosen
Indicates a temporal relationship specifying when an event occurs or how entities are ordered or related in time.
- 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd8682d18c8190bbb35cc75c8a7c12 |
completed | March 20, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69bd845f41f88190b75b8b64b9e41862 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:02 p.m.