Triple
T33730842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MTRX |
E864269
|
entity |
| Predicate | operatesBetweenCity |
P202475
|
FINISHED |
| Object | Stockholm |
—
|
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: Stockholm | Statement: [MTRX, operatesBetweenCity, Stockholm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesBetweenCity Context triple: [MTRX, operatesBetweenCity, Stockholm]
-
A.
operatesBetween
Indicates a relationship where an action, process, or influence functions or takes effect in the space, interval, or context separating two entities.
-
B.
operatesBetweenRegion
Indicates a relationship in which an entity conducts operations or provides services that connect or span between two distinct regions.
-
C.
betweenCity
Indicates a spatial relationship where one entity is located in the area or position separating two specified cities.
-
D.
operatesCommuterServiceBetween
Indicates that an entity runs a commuter transportation service connecting two specified locations.
-
E.
hasCityPair
Indicates a relationship that links two cities considered as a connected or associated pair, often for purposes such as travel, trade, or comparison.
- 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_69f3498a64cc8190b4b414c67b280d93 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a00868083b081909afc3d8d4ad56b43 |
completed | May 10, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_6a0084f5f72c8190b08afa82690e322a |
completed | May 10, 2026, 1:15 p.m. |
| PDg | Predicate description generation | batch_6a00867f57a48190a4205a859a268998 |
completed | May 10, 2026, 1:22 p.m. |
Created at: May 1, 2026, 1:44 a.m.