Triple
T13587184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earlston |
E324597
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Melrose |
E107057
|
NE 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: Melrose | Statement: [Earlston, locatedNear, Melrose]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melrose Context triple: [Earlston, locatedNear, Melrose]
-
A.
Melrose
chosen
Melrose is a historic town in the Scottish Borders, best known for the ruins of Melrose Abbey and its picturesque setting near the River Tweed.
-
B.
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.
-
C.
Melrose
Melrose is a residential neighborhood located within the borough of Sayreville in Middlesex County, New Jersey.
-
D.
Melrose
Melrose is a suburban city in Middlesex County, Massachusetts, known for its residential neighborhoods and proximity to Boston.
-
E.
Melrose District
Melrose District is a trendy Los Angeles neighborhood known for its fashion boutiques, street art, and vibrant shopping and dining scene along Melrose Avenue.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb054c6008190839384ce26e8f71a |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bc148d08190821614a866d1a7f0 |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.