Triple
T14601477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stange |
E342714
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object | Tangen |
E1061043
|
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: Tangen | Statement: [Stange, neighboringMunicipality, Tangen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tangen Context triple: [Stange, neighboringMunicipality, Tangen]
-
A.
Tangen
Tangen is a former settlement in Norway that was incorporated into the city of Drammen through a municipal merger.
-
B.
Tangen
chosen
Tangen is a village in Stange municipality in Innlandet county, Norway, known for its residential character and proximity to the lake Mjøsa.
-
C.
Tunasan
Tunasan is a barangay and district in the southern part of Muntinlupa City in Metro Manila, Philippines.
-
D.
Tigak
Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
-
E.
Letang
Letang is the surname of Kris Letang, a professional ice hockey defenseman best known for his long career with the NHL’s Pittsburgh Penguins.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb438748081908020ce04b869866a |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd94cc9fbc819090ae4efe9bc618aa |
completed | May 8, 2026, 7:46 a.m. |
Created at: April 10, 2026, 1:25 a.m.