Triple
T36268270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halfweg |
E892289
|
entity |
| Predicate | roadDistanceToHaarlem |
P185073
|
FINISHED |
| Object | approximately 10 kilometres |
—
|
LITERAL 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: approximately 10 kilometres | Statement: [Halfweg, roadDistanceToHaarlem, approximately 10 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToHaarlem Context triple: [Halfweg, roadDistanceToHaarlem, approximately 10 kilometres]
-
A.
roadDistanceToUtrecht_km
Indicates the distance in kilometers between an entity and Utrecht when traveling by road.
-
B.
distanceToAmsterdam
Indicates the spatial distance between a given location and the city of Amsterdam.
-
C.
distanceToRotterdam
Indicates the measured distance between a given entity’s location and the city of Rotterdam.
-
D.
distanceToDenHaagCentraal
Indicates the measured distance between a given location and Den Haag Centraal station.
-
E.
distanceToUtrecht
Indicates the spatial distance between a given entity and the location of Utrecht.
- F. None of above. chosen
Provenance (4 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_69f76e4699188190af045b11a840ce31 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb1d6b70819091227bd011734d19 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7ba6c27e081908868a2b50d1d603c |
completed | May 3, 2026, 9:13 p.m. |
Created at: May 3, 2026, 4:09 p.m.