Triple
T22751250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A5 motorway (Portugal) |
E562703
|
entity |
| Predicate | hasJunctionWith |
P1018
|
FINISHED |
| Object | CREL |
—
|
NE NERFINISHED |
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: CREL | Statement: [A5 motorway (Portugal), hasJunctionWith, CREL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CREL Context triple: [A5 motorway (Portugal), hasJunctionWith, CREL]
-
A.
CREL
CREL is the stock ticker symbol for Corel Corporation, a software company best known for products like CorelDRAW and WordPerfect.
-
B.
Crey
Crey is a shortened form or nickname for the given name Creighton.
-
C.
CRUE
CRUE is the main association representing Spanish universities, coordinating and promoting their interests in higher education and research.
-
D.
Kreli
Kreli was a Xhosa military leader who played a significant role in resisting British colonial forces during the Ninth Frontier War in South Africa.
-
E.
A9 (CREL)
chosen
A9 (CREL) is a major ring road motorway in the Lisbon metropolitan area that helps divert traffic around the city and connects several surrounding municipalities, including Odivelas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b9ac348190bff4dc470931f7e3 |
completed | April 29, 2026, 3:23 a.m. |
Created at: April 17, 2026, 3:24 p.m.