Triple
T15567724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ovar |
E374158
|
entity |
| Predicate | municipalSeat |
P15510
|
FINISHED |
| Object |
Ovar (city)
Ovar (city) is a coastal municipality in northern Portugal known for its beaches, traditional Carnival celebrations, and distinctive azulejo-tiled architecture.
|
E1165519
|
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: Ovar (city) | Statement: [Ovar, municipalSeat, Ovar (city)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ovar (city) Context triple: [Ovar, municipalSeat, Ovar (city)]
-
A.
Boucha
Boucha is the surname of Henry Boucha, a notable American ice hockey player of Ojibwe heritage.
-
B.
Issoudun
Issoudun is a historic commune in central France known for its medieval architecture and location within the Indre department.
-
C.
Arzew
Arzew is a coastal town and port in northwestern Algeria, historically significant as a strategic Mediterranean harbor and later as a center for the country’s oil and gas industry.
-
D.
Badrashin city
Badrashin city is an urban center in Giza Governorate, Egypt, known for its proximity to several important archaeological and historical sites from ancient Egypt.
-
E.
Yasmine City
Yasmine City is a modern seaside resort area in Hammamet, Tunisia, known for its hotels, marina, beaches, and tourist attractions.
- 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: Ovar (city) Triple: [Ovar, municipalSeat, Ovar (city)]
Generated description
Ovar (city) is a coastal municipality in northern Portugal known for its beaches, traditional Carnival celebrations, and distinctive azulejo-tiled architecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ovar (city) Target entity description: Ovar (city) is a coastal municipality in northern Portugal known for its beaches, traditional Carnival celebrations, and distinctive azulejo-tiled architecture.
-
A.
Boucha
Boucha is the surname of Henry Boucha, a notable American ice hockey player of Ojibwe heritage.
-
B.
Issoudun
Issoudun is a historic commune in central France known for its medieval architecture and location within the Indre department.
-
C.
Arzew
Arzew is a coastal town and port in northwestern Algeria, historically significant as a strategic Mediterranean harbor and later as a center for the country’s oil and gas industry.
-
D.
Badrashin city
Badrashin city is an urban center in Giza Governorate, Egypt, known for its proximity to several important archaeological and historical sites from ancient Egypt.
-
E.
Yasmine City
Yasmine City is a modern seaside resort area in Hammamet, Tunisia, known for its hotels, marina, beaches, and tourist attractions.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04dde90b081908284d9258d4462e3 |
completed | April 16, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c4219a081909acca9f783ecd44b |
completed | May 9, 2026, 3:01 p.m. |
| NEDg | Description generation | batch_69ff50d54960819089491ccb580784b8 |
completed | May 9, 2026, 3:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff5208e9a08190b4a6f4157cf3c237 |
completed | May 9, 2026, 3:26 p.m. |
Created at: April 10, 2026, 4:10 a.m.