Triple
T1209018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vijzelstraat |
E25955
|
entity |
| Predicate | crosses |
P416
|
FINISHED |
| Object | Singel |
E3947
|
NE 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: Singel | Statement: [Vijzelstraat, crosses, Singel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Singel Context triple: [Vijzelstraat, crosses, Singel]
-
A.
Singel
chosen
Singel is a historic canal in Amsterdam that once served as the city’s medieval moat and now forms part of its iconic canal belt.
-
B.
Sing
Sing is a 2016 animated musical comedy film featuring a group of anthropomorphic animals who enter a singing competition, produced by Illumination Entertainment.
-
C.
A Song
"A Song" is a track by Greek composer Vangelis featured on his 1979 electronic music album "Earth."
-
D.
Song to Song
Song to Song is a 2017 experimental romantic drama film directed by Terrence Malick, known for its impressionistic narrative, Austin music-scene setting, and fluid, visually striking cinematography.
-
E.
Solo
Solo is a city in Central Java, Indonesia, renowned as a major center of traditional Javanese culture and batik craftsmanship.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bde30ce08190ab60a181ad2d321d |
completed | March 1, 2026, 10:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8319d0e88190977a4d434b209f11 |
completed | March 7, 2026, 7:57 p.m. |
Created at: March 1, 2026, 7:46 p.m.