Triple
T6835326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leidsevaart |
E157434
|
entity |
| Predicate | runsThrough |
P416
|
FINISHED |
| Object | Lisse |
E39153
|
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: Lisse | Statement: [Leidsevaart, runsThrough, Lisse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lisse Context triple: [Leidsevaart, runsThrough, Lisse]
-
A.
Lisse
chosen
Lisse is a town in the western Netherlands renowned for its flower bulb fields and the famous Keukenhof gardens.
-
B.
Lisses
Lisses is a commune in the southern suburbs of Paris, located in the Essonne department in the Île-de-France region of northern France.
-
C.
Litzlitz
Litzlitz is a language of Vanuatu, also known as Naman, spoken by a small community on the island of Malakula.
-
D.
Lys
The Lys is a river in northern France and western Belgium that flows through cities like Ghent and is known for its historical role in trade and the textile industry.
-
E.
Lys
Lys is a wealthy and decadent island city-state in the world of *A Song of Ice and Fire* known for its pleasure houses, skilled courtesans, and distinctive Valyrian-descended population.
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d67a9ff88190b0d86331b3ea06aa |
completed | March 27, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723fd50c88190af005fd58ca0aee6 |
completed | March 28, 2026, 12:42 a.m. |
Created at: March 27, 2026, 2:19 p.m.