Triple
T33629606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amstel interchange |
E861514
|
entity |
| Predicate | connectsToUrbanArea |
P97106
|
FINISHED |
| Object | Amsterdam city |
—
|
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: Amsterdam city | Statement: [Amstel interchange, connectsToUrbanArea, Amsterdam city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsToUrbanArea Context triple: [Amstel interchange, connectsToUrbanArea, Amsterdam city]
-
A.
connectsToUrbanCenter
chosen
Indicates that one entity has a direct or functional linkage to an urban center, such as through infrastructure, services, or regular interaction.
-
B.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
-
C.
appliesToUrbanArea
Indicates that the relationship, rule, or condition is specifically relevant or applicable to an urban area.
-
D.
hasUrbanAreaApprox
Indicates an approximate measure or estimate of the size or extent of an entity’s urban area.
-
E.
withinUrbanArea
Indicates that one entity is located inside the spatial boundaries of an urban area associated with another entity.
- 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_69f34981c54c81909b33c3fa2208a52d |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff255b84788190a94682f4efe1d0b8 |
completed | May 9, 2026, 12:15 p.m. |
| PD | Predicate disambiguation | batch_69ff24f3ab108190bb017a656cff3d82 |
completed | May 9, 2026, 12:13 p.m. |
Created at: May 1, 2026, 1:41 a.m.