Triple
T17645549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Binnenstad Tiel |
E429347
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Tiel |
—
|
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: Tiel | Statement: [Binnenstad Tiel, locatedIn, Tiel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiel Context triple: [Binnenstad Tiel, locatedIn, Tiel]
-
A.
Tiel
chosen
Tiel is a historic Dutch city situated along the River Waal, known for its fruit cultivation and role as a regional trade center in the province of Gelderland.
-
B.
Tjuchem
Tjuchem is a small village in the province of Groningen in the Netherlands, known for its rural character and agricultural surroundings.
-
C.
Tiba
Tiba is a modern planned city in Egypt’s Luxor Governorate, developed to accommodate population growth and support regional economic and urban expansion.
-
D.
Tachov
Tachov is a town in western Czechia that serves as an administrative center and local hub within the Plzeň Region.
-
E.
Taucha
Taucha is a small town in the German state of Saxony, located just northeast of Leipzig and closely integrated into its urban and economic area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46e382ba88190af19d0e3b8c8cadd |
completed | April 19, 2026, 5:55 a.m. |
Created at: April 10, 2026, 6:04 a.m.