Triple
T27875487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marius Josipović |
E704918
|
entity |
| Predicate | hasFormerCellmate |
P180019
|
FINISHED |
| Object | Pete Murphy |
—
|
NE NERFINISHED |
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: Pete Murphy | Statement: [Marius Josipović, hasFormerCellmate, Pete Murphy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerCellmate Context triple: [Marius Josipović, hasFormerCellmate, Pete Murphy]
-
A.
hasFormerInmate
Indicates that an entity previously housed or supervised an individual who was once an inmate there.
-
B.
hasBeenImprisoned
Indicates that an entity has been confined or incarcerated in a prison or similar detention facility at some point in time.
-
C.
hasBeenImprisonedBy
Indicates that one entity has been confined or incarcerated under the authority or control of another entity.
-
D.
hasPrison
Indicates that one entity possesses, contains, or is the location of a prison associated with another entity.
-
E.
hasPrisoners
Indicates that an entity holds or contains one or more individuals who are imprisoned or detained.
- 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_69ef84111bb4819084298f994b31c62f |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
| PDg | Predicate description generation | batch_69f730890a008190a882f7828f1c9162 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 27, 2026, 6:27 p.m.