Triple
T23524534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melrose Highlands |
E574596
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | City of Melrose |
—
|
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: City of Melrose | Statement: [Melrose Highlands, partOf, City of Melrose]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Melrose Context triple: [Melrose Highlands, partOf, City of Melrose]
-
A.
Melrose
Melrose is a residential neighborhood located within the borough of Sayreville in Middlesex County, New Jersey.
-
B.
Melrose
Melrose is an affluent, tree-lined suburb in northern Johannesburg, South Africa, known for its upmarket residential areas, offices, and shopping centers.
-
C.
Melrose
chosen
Melrose is a suburban city in Middlesex County, Massachusetts, known for its residential neighborhoods and proximity to Boston.
-
D.
Melrose
Melrose is a small rural community located within the municipality of Middlesex Centre in southwestern Ontario, Canada.
-
E.
Melrose
Melrose is a residential and commercial neighborhood in the South Bronx of New York City known for its dense urban character and diverse community.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1ac72bfb88190b7da3837e66e851c |
completed | April 29, 2026, 7 a.m. |
Created at: April 17, 2026, 6:09 p.m.