Triple
T29898133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerald Lambeau |
E759332
|
entity |
| Predicate | helpsArrange |
P67492
|
FINISHED |
| Object | Will Hunting's probation deal |
—
|
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: Will Hunting's probation deal | Statement: [Gerald Lambeau, helpsArrange, Will Hunting's probation deal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpsArrange Context triple: [Gerald Lambeau, helpsArrange, Will Hunting's probation deal]
-
A.
arranges
Indicates that one entity organizes, coordinates, or puts in order some event, objects, or circumstances involving another entity.
-
B.
arrangement
Indicates a relationship where entities are organized, ordered, or positioned in a particular configuration or sequence relative to one another.
-
C.
commonlyArrangedFor
Indicates that one entity is typically organized, scheduled, or set up on behalf of another entity.
-
D.
canBeArrangedFor
Indicates that one entity is able to be scheduled, organized, or set up on behalf of or for the benefit of another entity.
-
E.
helpsOrchestrate
chosen
Indicates involvement in coordinating, organizing, or managing the execution of an activity or process, often in collaboration with others.
- 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_69f2245f1cf88190978c70d1a1d2cb73 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6772d534c8190be386d44e7f60a4e |
completed | May 2, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:05 p.m.