Triple
T3415582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valencia Cathedral |
E71999
|
entity |
| Predicate | hasBellTower |
P2495
|
FINISHED |
| Object |
Micalet
Micalet is the iconic Gothic bell tower of Valencia Cathedral and one of the most recognizable landmarks in the city of Valencia, Spain.
|
E354510
|
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: Micalet | Statement: [Valencia Cathedral, hasBellTower, Micalet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Micalet Context triple: [Valencia Cathedral, hasBellTower, Micalet]
-
A.
Micali
Micali is an Italian surname most notably associated with Silvio Micali, a Turing Award–winning computer scientist and cryptographer.
-
B.
Mora
Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
-
C.
Martos
Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
-
D.
Cimla
Cimla is a residential suburb and community situated near the town of Neath in Neath Port Talbot, South Wales.
-
E.
Makatsch
Makatsch is the surname of German actress and television presenter Heike Makatsch, known for her roles in films such as "Love Actually" and "Resident Evil."
- 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: Micalet Triple: [Valencia Cathedral, hasBellTower, Micalet]
Generated description
Micalet is the iconic Gothic bell tower of Valencia Cathedral and one of the most recognizable landmarks in the city of Valencia, Spain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Micalet Target entity description: Micalet is the iconic Gothic bell tower of Valencia Cathedral and one of the most recognizable landmarks in the city of Valencia, Spain.
-
A.
Micali
Micali is an Italian surname most notably associated with Silvio Micali, a Turing Award–winning computer scientist and cryptographer.
-
B.
Mora
Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
-
C.
Martos
Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
-
D.
Cimla
Cimla is a residential suburb and community situated near the town of Neath in Neath Port Talbot, South Wales.
-
E.
Makatsch
Makatsch is the surname of German actress and television presenter Heike Makatsch, known for her roles in films such as "Love Actually" and "Resident Evil."
- 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_69ad85ad38e48190b7660c5118a35289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb929b8ec8190aef431ec8ea2cf80 |
completed | March 8, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34be316a88190a15cb1e9f31b57d0 |
completed | March 12, 2026, 11:27 p.m. |
| NEDg | Description generation | batch_69b34e4a1db88190b30362f4147754dc |
completed | March 12, 2026, 11:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b34ebb55bc81909eabf629b688714e |
completed | March 12, 2026, 11:39 p.m. |
Created at: March 8, 2026, 3:15 p.m.