Triple
T38078156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Young Man in "Following" |
E950775
|
entity |
| Predicate | becomesInvolvedIn |
P74692
|
FINISHED |
| Object | burglary |
—
|
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: burglary | Statement: [The Young Man in "Following", becomesInvolvedIn, burglary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becomesInvolvedIn Context triple: [The Young Man in "Following", becomesInvolvedIn, burglary]
-
A.
hasBeenInvolvedIn
chosen
Indicates that an entity has participated in, taken part in, or been connected to a particular event, activity, or situation.
-
B.
mayBeInvolvedIn
Indicates that an entity has a possible, but not certain, participation or role in a particular event, activity, or situation.
-
C.
oftenInvolvedWith
Indicates that one entity frequently participates in or is commonly associated with activities, events, or situations involving another entity.
-
D.
closelyInvolvedWith
Indicates a relationship in which one entity is deeply and actively engaged with another’s activities, decisions, or affairs.
-
E.
involves
Indicates that an entity participates in, is a part of, or is implicated within a particular event, process, or relationship.
- 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_69f76f02a6c48190a94f3c0b3ee90cf2 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc4748843c8190931432653be4890c |
completed | May 7, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69fc45646ce481908caf292ff9f06e15 |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 3, 2026, 4:21 p.m.