Triple
T7371653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna LoPizzo |
E170018
|
entity |
| Predicate | employerLocation |
P1527
|
FINISHED |
| Object | Lawrence, Massachusetts |
—
|
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: Lawrence, Massachusetts | Statement: [Anna LoPizzo, employerLocation, Lawrence, Massachusetts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerLocation Context triple: [Anna LoPizzo, employerLocation, Lawrence, Massachusetts]
-
A.
recruitmentLocation
Indicates the place or geographic area where the recruitment or hiring of individuals occurs.
-
B.
locationOfWork
chosen
Indicates the place or site where an entity performs its work or carries out its professional activities.
-
C.
organizationLocatedAt
Indicates that an organization is situated or based at a specific geographic location or address.
-
D.
agencyLocatedIn
Indicates that an agency is situated or based within a specific geographic or administrative location.
-
E.
employerHeadquarters
Indicates the location where an employer’s main corporate offices or central administrative operations are based.
- 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f18451d88190ad4a2674279bb703 |
completed | March 27, 2026, 9:07 p.m. |
| PD | Predicate disambiguation | batch_69c6f02ee3e08190a7a00c981129b22c |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:07 p.m.