Triple
T33709731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim Worth |
E863700
|
entity |
| Predicate | formerWorkLocation |
P190281
|
FINISHED |
| Object | London |
—
|
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: London | Statement: [Jim Worth, formerWorkLocation, London]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerWorkLocation Context triple: [Jim Worth, formerWorkLocation, London]
-
A.
formerEmployer
Indicates that one entity previously employed the other but no longer does so.
-
B.
locationOfWork
Indicates the place or site where an entity performs its work or carries out its professional activities.
-
C.
formerLocationNow
Indicates that an entity used to be located at a place in the past but is no longer located there now.
-
D.
workedInLocation
chosen
Indicates that an entity performed work or held a job in a specified geographic location or place.
-
E.
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).
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ffc89596d08190b97bd60b45c7f9c0 |
completed | May 9, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69ffc81ba5dc8190ae94d44e2284948f |
completed | May 9, 2026, 11:49 p.m. |
Created at: May 1, 2026, 1:43 a.m.