Triple
T14941538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luther McDonald |
E372541
|
entity |
| Predicate | hasBeenIn |
P42984
|
FINISHED |
| Object | prison |
—
|
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: prison | Statement: [Luther McDonald, hasBeenIn, prison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeenIn Context triple: [Luther McDonald, hasBeenIn, prison]
-
A.
wasIn
Indicates that an entity existed, occurred, or was located within a particular place or context during a specified time or situation.
-
B.
hasHad
Indicates that an entity previously experienced, possessed, or was involved in something at some point in the past.
-
C.
hasMet
Indicates that one entity has encountered or come into contact with another entity at least once.
-
D.
hasPreviouslyBeenHeldIn
chosen
Indicates that an entity was located, confined, or kept in a particular place or container at some time in the past.
-
E.
visitedDuring
Indicates that one entity was present at or traveled to another entity within a specified time period or event.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68c1df0819084c0cd61b207d398 |
completed | April 15, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69de9a588c2c8190b1245a1c406f447c |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:38 a.m.