Triple
T24118055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John May |
E597573
|
entity |
| Predicate | locatedInWorkplace |
P146199
|
FINISHED |
| Object | Chicago garage |
—
|
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: Chicago garage | Statement: [John May, locatedInWorkplace, Chicago garage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInWorkplace Context triple: [John May, locatedInWorkplace, Chicago garage]
-
A.
locationInWork
Indicates that one entity specifies the place or setting where another entity occurs, is situated, or takes place within a particular work (e.g., a scene’s location in a film or a chapter’s setting in a book).
-
B.
residesInWork
Indicates that a person or entity lives or is based within the location, setting, or environment defined by a particular work (such as a book, film, or other creative piece).
-
C.
placeInWork
Indicates that one entity is located or occurs within the spatial or structural context of another entity in a work.
-
D.
appliedToWorkCurrentLocation
Indicates that an application was submitted for a job or position at the entity’s current work location.
-
E.
associatedWithWorkplace
chosen
Indicates a relationship where an entity has a connection or affiliation with a particular workplace or place of employment.
- 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_69e288c74200819098ab875b592cb39f |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dee091c48190a55d36f28c332749 |
completed | April 29, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:05 p.m.