Triple
T2017854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southwest Philadelphia |
E44036
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Eastwick |
E182359
|
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: Eastwick | Statement: [Southwest Philadelphia, contains, Eastwick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eastwick Context triple: [Southwest Philadelphia, contains, Eastwick]
-
A.
Eastwick
chosen
Eastwick is a residential neighborhood in Southwest Philadelphia known for its proximity to the airport, extensive wetlands, and diverse community.
-
B.
Melrose
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.
-
C.
Welhaven
Welhaven is a Norwegian surname most notably associated with the 19th-century poet and critic Johan Sebastian Welhaven.
-
D.
Melrose Park
Melrose Park is a local public park and recreational area located in Chelsea, Alabama.
-
E.
Woodhaven
Woodhaven is a residential neighborhood in the borough of Queens, New York City, known for its diverse community and proximity to major transit lines and Forest Park.
- 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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8ce71788190ac21beff10b08122 |
completed | March 7, 2026, 5:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0af1547481909d5f2ca9c4715ace |
completed | March 8, 2026, 11:49 p.m. |
Created at: March 4, 2026, 7:38 p.m.