Triple
T3137526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De Dam |
E65568
|
entity |
| Predicate | distanceToAmsterdamCentraalStation |
P32616
|
FINISHED |
| Object | about 750 meters |
—
|
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: about 750 meters | Statement: [De Dam, distanceToAmsterdamCentraalStation, about 750 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAmsterdamCentraalStation Context triple: [De Dam, distanceToAmsterdamCentraalStation, about 750 meters]
-
A.
distanceToAmsterdamCentraal
chosen
Indicates the physical distance between a given location and Amsterdam Centraal station.
-
B.
distanceFromParisSaintLazare
Indicates the physical distance between a given place and Paris Saint-Lazare railway station.
-
C.
distanceToBerlin
Indicates the spatial distance between a given entity’s location and the city of Berlin.
-
D.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
-
E.
cityDistanceFromBrussels_km
Indicates the distance, measured in kilometers, between a given city and Brussels.
- F. None of above.
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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada574509c81908a88bb10ea35516d |
completed | March 8, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69ad9df840088190a26a1516f4c1f056 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:05 p.m.