Triple
T2083403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Sydney |
E45293
|
entity |
| Predicate | campus |
P269
|
FINISHED |
| Object | Darlington |
E149816
|
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: Darlington | Statement: [University of Sydney, campus, Darlington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darlington Context triple: [University of Sydney, campus, Darlington]
-
A.
Darlington
Darlington is a surname of English origin borne by various notable individuals across fields such as engineering, science, and public life.
-
B.
Darlington
chosen
Darlington is a market town and borough in County Durham, England, historically known for its pioneering role in railway development.
-
C.
Alston
Alston is a small historic market town in Cumbria, England, known for its scenic Pennine landscape and claim to be one of the highest market settlements in the country.
-
D.
Rock Hill
Rock Hill is a rapidly growing city in northern South Carolina known for its proximity to Charlotte, diverse economy, and strong sports and educational institutions.
-
E.
Durham
Durham is a historic cathedral city in northeast England known for its Norman architecture and prestigious university.
- 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_69a8891869c88190a02643e3bb746f59 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba524b60819089a11957ce6dbc4b |
completed | March 7, 2026, 5:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae273d3f5881909fa6d935fa85c225 |
completed | March 9, 2026, 1:49 a.m. |
Created at: March 4, 2026, 7:41 p.m.