Triple
T14029885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kraaifontein |
E337558
|
entity |
| Predicate | hasTransportConnection |
P845
|
FINISHED |
| Object | R101 road |
E784013
|
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: R101 road | Statement: [Kraaifontein, hasTransportConnection, R101 road]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: R101 road Context triple: [Kraaifontein, hasTransportConnection, R101 road]
-
A.
R107 road
The R107 road is a regional route in County Dublin, Ireland, connecting parts of north Dublin city to suburban areas including Kinsealy and Malahide.
-
B.
R102 road
chosen
The R102 road is a regional route in South Africa that largely follows the old alignment of the N2 highway, connecting various coastal and inland towns along the eastern seaboard.
-
C.
R106 road
The R106 road is a regional route in County Dublin, Ireland, linking coastal and suburban areas including the town of Swords.
-
D.
N10 road
The N10 road is a national secondary route in Ireland that connects the M9 motorway to the city of Kilkenny.
-
E.
N10 road
The N10 road is a major French national highway that runs southwest from the Paris region toward Bordeaux, serving as an important long-distance route through western France.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fa9f8248190930954d609dee5f1 |
completed | April 14, 2026, 12:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc335a474819084c310b10e0ded9a |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:20 p.m.