Triple
T27298169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pajala |
E688824
|
entity |
| Predicate | distanceToLulea_km |
P199208
|
FINISHED |
| Object | about 200 |
—
|
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 200 | Statement: [Pajala, distanceToLulea_km, about 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLulea_km Context triple: [Pajala, distanceToLulea_km, about 200]
-
A.
distanceFromUppsala_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Uppsala.
-
B.
distanceToLappeenranta_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Lappeenranta.
-
C.
distanceFromNyköping
Indicates the spatial distance separating an entity from the location of Nyköping.
-
D.
distanceToOulu_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Oulu.
-
E.
distanceToHelsinki_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Helsinki.
- 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_69ef355a96308190a2bed991525fb278 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69ff2636e2bc8190bba91eff91431c6e |
completed | May 9, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69ff25c65be48190868480d94e1c4e89 |
completed | May 9, 2026, 12:17 p.m. |
| PDg | Predicate description generation | batch_69ff263632608190a99beb73608066d8 |
completed | May 9, 2026, 12:19 p.m. |
Created at: April 27, 2026, 11:20 a.m.