Triple
T3701760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troms |
E80793
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Hansnes
Hansnes is a small coastal village in northern Norway that serves as an administrative and ferry hub for the surrounding islands in Troms.
|
E381851
|
NE FINISHED |
How this triple was built (4 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: Hansnes | Statement: [Troms, containsTown, Hansnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hansnes Context triple: [Troms, containsTown, Hansnes]
-
A.
Iittala
Iittala is a Finnish design brand renowned for its high-quality glassware and timeless Scandinavian tableware and home objects.
-
B.
Blomberg
Blomberg is a small town in the Lippe district of North Rhine-Westphalia, Germany, known as the birthplace of former German chancellor Gerhard Schröder.
-
C.
Borregaard
Borregaard is a Norwegian biorefinery company that produces advanced and sustainable bio-based chemicals and materials from wood.
-
D.
Marcussen & Søn
Marcussen & Søn is a renowned Danish firm celebrated for crafting high-quality pipe organs for churches and concert halls worldwide.
-
E.
Petit & Fritsen
Petit & Fritsen is a historic Dutch bell foundry renowned for casting church bells and carillons used in notable towers and monuments worldwide.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hansnes Triple: [Troms, containsTown, Hansnes]
Generated description
Hansnes is a small coastal village in northern Norway that serves as an administrative and ferry hub for the surrounding islands in Troms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hansnes Target entity description: Hansnes is a small coastal village in northern Norway that serves as an administrative and ferry hub for the surrounding islands in Troms.
-
A.
Iittala
Iittala is a Finnish design brand renowned for its high-quality glassware and timeless Scandinavian tableware and home objects.
-
B.
Blomberg
Blomberg is a small town in the Lippe district of North Rhine-Westphalia, Germany, known as the birthplace of former German chancellor Gerhard Schröder.
-
C.
Borregaard
Borregaard is a Norwegian biorefinery company that produces advanced and sustainable bio-based chemicals and materials from wood.
-
D.
Marcussen & Søn
Marcussen & Søn is a renowned Danish firm celebrated for crafting high-quality pipe organs for churches and concert halls worldwide.
-
E.
Petit & Fritsen
Petit & Fritsen is a historic Dutch bell foundry renowned for casting church bells and carillons used in notable towers and monuments worldwide.
- F. None of above. chosen
Provenance (5 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc547c1848190a1ece46c59b7c43d |
completed | March 8, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4cdf53190819098529d11a5a3c7a8 |
completed | March 14, 2026, 2:54 a.m. |
| NEDg | Description generation | batch_69b4cf799ae88190bbf821f4c4500031 |
completed | March 14, 2026, 3:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4d0057fe8819092a40732324f88c9 |
completed | March 14, 2026, 3:03 a.m. |
Created at: March 8, 2026, 3:33 p.m.