Triple
T10166720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College Walk |
E235221
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | College Green |
E214284
|
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: College Green | Statement: [College Walk, near, College Green]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: College Green Context triple: [College Walk, near, College Green]
-
A.
College Green
chosen
College Green is a historic public square in central Dublin, Ireland, known as a civic and commercial hub surrounded by landmark buildings including Trinity College Dublin.
-
B.
College Green
College Green is a historic open space in Westminster, London, commonly used as a backdrop for political interviews and media broadcasts near the UK Parliament.
-
C.
College Holiday
College Holiday is a 1936 American musical comedy film featuring Gracie Allen in a prominent comedic role.
-
D.
Young High School
Young High School is an educational institution serving secondary-level students in the community of Young.
-
E.
College Track
College Track is a U.S.-based nonprofit organization that supports underserved students through high school and college with academic, financial, and mentoring resources to improve college completion rates.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec6e016c81909ded2a16b839c405 |
completed | April 2, 2026, 4:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d300e06bbc8190a51f872eccac8f40 |
completed | April 6, 2026, 12:40 a.m. |
Created at: March 30, 2026, 9:10 p.m.