Triple
T38676858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hank Lawson |
E943770
|
entity |
| Predicate | formerWorkplace |
P1910
|
FINISHED |
| Object | Brooklyn hospital emergency room |
—
|
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: Brooklyn hospital emergency room | Statement: [Hank Lawson, formerWorkplace, Brooklyn hospital emergency room]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerWorkplace Context triple: [Hank Lawson, formerWorkplace, Brooklyn hospital emergency room]
-
A.
formerEmployer
chosen
Indicates that one entity previously employed the other but no longer does so.
-
B.
workAt
Indicates that an entity is employed by or performs work for a particular organization, company, or place.
-
C.
previousCorporateAffiliation
Indicates that an entity was formerly employed by, associated with, or part of a specified corporate organization before its current status or affiliation.
-
D.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
E.
locationOfWork
Indicates the place or site where an entity performs its work or carries out its professional activities.
- 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_69f76eec28708190b9c82a505fc278e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a016b2629c48190befb10581560d58f |
completed | May 11, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_6a0167d5a2088190a68dbd2b87f73e80 |
completed | May 11, 2026, 5:23 a.m. |
Created at: May 3, 2026, 4:33 p.m.