Triple
T4504692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalhousie University |
E101304
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Dal |
E101304
|
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: Dal | Statement: [Dalhousie University, shortName, Dal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dal Context triple: [Dalhousie University, shortName, Dal]
-
A.
Dal
chosen
Dal is the commonly used short form for Dalhousie University, a major public research university in Halifax, Nova Scotia, Canada.
-
B.
Daraw
Daraw is a town in southern Egypt known historically as a regional trading center, particularly for its camel market, within the Aswan Governorate.
-
C.
Dara
Dara is a given name most prominently associated with Dara Khosrowshahi, the Iranian-American businessman and CEO of Uber.
-
D.
Des
Des is a given name, typically used as a shortened form of Desmond.
-
E.
Den
Den was a prominent pharaoh of Egypt’s First Dynasty, known for early administrative innovations and military campaigns that helped consolidate the young Egyptian state.
- 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_69bd43d175248190894dc58b5b395c26 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56fe17608190ae5dc27052b7c337 |
completed | March 20, 2026, 2:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd6f958de0819082d17c165d25e703 |
completed | March 20, 2026, 4:02 p.m. |
Created at: March 20, 2026, 1:01 p.m.