Triple
T32695852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Ramseur |
E836004
|
entity |
| Predicate | roleInIncident |
P202085
|
FINISHED |
| Object | alleged attempted robber |
—
|
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: alleged attempted robber | Statement: [James Ramseur, roleInIncident, alleged attempted robber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInIncident Context triple: [James Ramseur, roleInIncident, alleged attempted robber]
-
A.
roleInInvestigation
Indicates that an entity holds a specific function, capacity, or responsibility within the context of a particular investigation.
-
B.
roleInOperation
Indicates that an entity holds a specific function, duty, or position within a particular operation or activity.
-
C.
roleInRescue
Indicates the specific function or responsibility an entity has within a rescue operation or event.
-
D.
roleInSafety
Indicates that an entity has a specific responsibility, function, or involvement related to ensuring safety within a given context.
-
E.
roleInDisasterMovie
Indicates that an entity has a specific acting or production role in a disaster-themed movie.
- 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_69f3493323288190a4e88251035fe96e |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a004d0b46148190bcec4ea67acfe170 |
completed | May 10, 2026, 9:16 a.m. |
| PD | Predicate disambiguation | batch_6a004c92283081909f229c1720af155a |
completed | May 10, 2026, 9:14 a.m. |
| PDg | Predicate description generation | batch_6a004d0a95548190ac822cd1d54edf42 |
completed | May 10, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:10 a.m.