Triple
T8910480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cap Gris-Nez |
E212168
|
entity |
| Predicate | nearbySettlement |
P350
|
FINISHED |
| Object |
Audinghen
Audinghen is a small coastal commune in northern France known for its proximity to the scenic Cap Gris-Nez headland on the English Channel.
|
E766652
|
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: Audinghen | Statement: [Cap Gris-Nez, nearbySettlement, Audinghen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Audinghen Context triple: [Cap Gris-Nez, nearbySettlement, Audinghen]
-
A.
Audenarde
Audenarde (Oudenaarde) is a historic city in East Flanders, Belgium, known for its medieval architecture, tapestry production, and role in early modern European conflicts.
-
B.
Taradeau
Taradeau is a small commune in the Var department of southeastern France, known for its Provençal countryside, vineyards, and proximity to the Massif des Maures.
-
C.
Aulnat
Aulnat is a commune in central France situated in the Puy-de-Dôme department within the Auvergne region.
-
D.
Walhain
Walhain is a rural municipality in central Belgium known for its agricultural landscape and historic castle ruins.
-
E.
Radaur
Radaur is a town in the Yamunanagar district of Haryana, India, known primarily as a local commercial and educational center for surrounding rural areas.
- 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: Audinghen Triple: [Cap Gris-Nez, nearbySettlement, Audinghen]
Generated description
Audinghen is a small coastal commune in northern France known for its proximity to the scenic Cap Gris-Nez headland on the English Channel.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Audinghen Target entity description: Audinghen is a small coastal commune in northern France known for its proximity to the scenic Cap Gris-Nez headland on the English Channel.
-
A.
Audenarde
Audenarde (Oudenaarde) is a historic city in East Flanders, Belgium, known for its medieval architecture, tapestry production, and role in early modern European conflicts.
-
B.
Taradeau
Taradeau is a small commune in the Var department of southeastern France, known for its Provençal countryside, vineyards, and proximity to the Massif des Maures.
-
C.
Aulnat
Aulnat is a commune in central France situated in the Puy-de-Dôme department within the Auvergne region.
-
D.
Walhain
Walhain is a rural municipality in central Belgium known for its agricultural landscape and historic castle ruins.
-
E.
Radaur
Radaur is a town in the Yamunanagar district of Haryana, India, known primarily as a local commercial and educational center for surrounding rural areas.
- 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_69ca839255248190b43984294abd92ae |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc65227d008190b13ba162d0b3c9d1 |
completed | April 1, 2026, 12:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba36f8cc8190ab57ddc99b7219d1 |
completed | April 3, 2026, 1:01 p.m. |
| NEDg | Description generation | batch_69cfbade9330819096d4b0eeacdad6da |
completed | April 3, 2026, 1:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfbec2b8888190a0390168fdcef05f |
completed | April 3, 2026, 1:21 p.m. |
Created at: March 30, 2026, 6:55 p.m.