Triple
T6625842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamm |
E149797
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Neufchâteau |
E455901
|
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: Neufchâteau | Statement: [Hamm, hasTwinTown, Neufchâteau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neufchâteau Context triple: [Hamm, hasTwinTown, Neufchâteau]
-
A.
Neufchâteau
chosen
Neufchâteau is a small historic town in northeastern France known for its role as an administrative and commercial center in the Vosges region.
-
B.
Cresson
Cresson is a French surname most notably borne by Édith Cresson, who served as France’s first female prime minister.
-
C.
Cinnaminson
Cinnaminson is a suburban township in Burlington County, New Jersey, located along the Delaware River and within the Philadelphia metropolitan area.
-
D.
Mattersburg
Mattersburg is a small Austrian town that serves as an important local center in the eastern state of Burgenland.
-
E.
New Castle
New Castle is a historic riverfront city in northern Delaware known for its well-preserved colonial architecture and role as an early center of government in the state.
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af8187d881908b7a86f2cae5de23 |
completed | March 27, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e44d356c8190ad4f2a617c3de4af |
completed | March 27, 2026, 8:10 p.m. |
Created at: March 27, 2026, 1:58 p.m.