Triple
T4633143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nabeul Governorate |
E101463
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Menzel Horr
Menzel Horr is a town in northeastern Tunisia known for its agricultural surroundings and its location within the coastal Nabeul region.
|
E458672
|
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: Menzel Horr | Statement: [Nabeul Governorate, hasCity, Menzel Horr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Menzel Horr Context triple: [Nabeul Governorate, hasCity, Menzel Horr]
-
A.
Menzel
Menzel is the surname of Idina Menzel, the American actress and singer best known for her roles in Broadway musicals and the film "Frozen."
-
B.
Thoosa
Thoosa is a minor sea nymph in Greek mythology, known primarily as the mother of the Cyclops Polyphemus by the sea god Poseidon.
-
C.
Modrow
Modrow is a German surname most notably associated with Hans Modrow, the last communist premier of East Germany.
-
D.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
E.
Mistinguett
Mistinguett was a famous French actress and singer of the early 20th century, celebrated as one of Paris’s most iconic music-hall stars.
- 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: Menzel Horr Triple: [Nabeul Governorate, hasCity, Menzel Horr]
Generated description
Menzel Horr is a town in northeastern Tunisia known for its agricultural surroundings and its location within the coastal Nabeul region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Menzel Horr Target entity description: Menzel Horr is a town in northeastern Tunisia known for its agricultural surroundings and its location within the coastal Nabeul region.
-
A.
Menzel
Menzel is the surname of Idina Menzel, the American actress and singer best known for her roles in Broadway musicals and the film "Frozen."
-
B.
Thoosa
Thoosa is a minor sea nymph in Greek mythology, known primarily as the mother of the Cyclops Polyphemus by the sea god Poseidon.
-
C.
Modrow
Modrow is a German surname most notably associated with Hans Modrow, the last communist premier of East Germany.
-
D.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
E.
Mistinguett
Mistinguett was a famous French actress and singer of the early 20th century, celebrated as one of Paris’s most iconic music-hall stars.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a5d0de881909baacc5b991f5b53 |
completed | March 20, 2026, 2:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfac317248190a8886d59d2242acb |
completed | March 21, 2026, 1:56 a.m. |
| NEDg | Description generation | batch_69bdfceda19c8190909c21594ea792a0 |
completed | March 21, 2026, 2:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdfd7790748190b322d7f8109fa887 |
completed | March 21, 2026, 2:07 a.m. |
Created at: March 20, 2026, 1:13 p.m.