Triple
T9779468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ardennes department |
E237328
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Givet
Givet is a small fortified town in northeastern France near the Belgian border, known for its strategic location along the Meuse River.
|
E819821
|
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: Givet | Statement: [Ardennes department, contains, Givet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Givet Context triple: [Ardennes department, contains, Givet]
-
A.
Givan
Givan is a surname most notably associated with Paul Givan, a Northern Irish politician who has served as First Minister of Northern Ireland.
-
B.
Giæver
Giæver is a Norwegian surname borne by several notable figures in fields such as physics, literature, and public service.
-
C.
Donen
Donen is a surname most famously associated with Stanley Donen, the American film director and choreographer known for classic Hollywood musicals such as "Singin' in the Rain."
-
D.
Annett
Annett is a given name, typically a variant of Annette, used for females in various European countries.
-
E.
Gein
Gein is a metro station in Amsterdam, Netherlands, serving as one of the termini of the city's metro network.
- 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: Givet Triple: [Ardennes department, contains, Givet]
Generated description
Givet is a small fortified town in northeastern France near the Belgian border, known for its strategic location along the Meuse River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Givet Target entity description: Givet is a small fortified town in northeastern France near the Belgian border, known for its strategic location along the Meuse River.
-
A.
Givan
Givan is a surname most notably associated with Paul Givan, a Northern Irish politician who has served as First Minister of Northern Ireland.
-
B.
Giæver
Giæver is a Norwegian surname borne by several notable figures in fields such as physics, literature, and public service.
-
C.
Donen
Donen is a surname most famously associated with Stanley Donen, the American film director and choreographer known for classic Hollywood musicals such as "Singin' in the Rain."
-
D.
Annett
Annett is a given name, typically a variant of Annette, used for females in various European countries.
-
E.
Gein
Gein is a metro station in Amsterdam, Netherlands, serving as one of the termini of the city's metro network.
- 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_69ca84d975a08190aab25b02a89bdab3 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda13663f081909b95563038eb6485 |
completed | April 1, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bd28b0e48190984cf44d88f324d7 |
completed | April 5, 2026, 1:38 a.m. |
| NEDg | Description generation | batch_69d1be259b388190bf60b97a6be12715 |
completed | April 5, 2026, 1:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1bea090b48190ae903036cc79dded |
completed | April 5, 2026, 1:45 a.m. |
Created at: March 30, 2026, 8:27 p.m.