Triple
T18040685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penacova |
E431642
|
entity |
| Predicate | hasParish |
P35
|
FINISHED |
| Object |
Lorvão
Lorvão is a civil parish in the municipality of Penacova, in Portugal’s Coimbra District, known historically for the Monastery of Lorvão.
|
E1302606
|
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: Lorvão | Statement: [Penacova, hasParish, Lorvão]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorvão Context triple: [Penacova, hasParish, Lorvão]
-
A.
Lavangen
Lavangen is a small coastal municipality in Troms og Finnmark county in northern Norway, known for its fjord landscape and rural communities.
-
B.
Lessebo
Lessebo is a small locality and municipality in southern Sweden known for its traditional paper mill and glassmaking heritage.
-
C.
Lurøy
Lurøy is a coastal municipality in Nordland county, Norway, known for its scattered islands, fishing communities, and scenic Arctic landscapes.
-
D.
Valle-Hovin
Valle-Hovin is a residential and recreational neighborhood in Oslo, Norway, known for its sports facilities and event venues.
-
E.
Vanylven
Vanylven is a coastal municipality in western Norway known for its fjords, mountains, and rural communities.
- 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: Lorvão Triple: [Penacova, hasParish, Lorvão]
Generated description
Lorvão is a civil parish in the municipality of Penacova, in Portugal’s Coimbra District, known historically for the Monastery of Lorvão.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lorvão Target entity description: Lorvão is a civil parish in the municipality of Penacova, in Portugal’s Coimbra District, known historically for the Monastery of Lorvão.
-
A.
Lavangen
Lavangen is a small coastal municipality in Troms og Finnmark county in northern Norway, known for its fjord landscape and rural communities.
-
B.
Lessebo
Lessebo is a small locality and municipality in southern Sweden known for its traditional paper mill and glassmaking heritage.
-
C.
Lurøy
Lurøy is a coastal municipality in Nordland county, Norway, known for its scattered islands, fishing communities, and scenic Arctic landscapes.
-
D.
Valle-Hovin
Valle-Hovin is a residential and recreational neighborhood in Oslo, Norway, known for its sports facilities and event venues.
-
E.
Vanylven
Vanylven is a coastal municipality in western Norway known for its fjords, mountains, and rural communities.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4bfee78048190b3fada0eb3d28c77 |
completed | April 19, 2026, 11:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0349b8930c8190bbd871393b4b949e |
completed | May 12, 2026, 3:39 p.m. |
| NEDg | Description generation | batch_6a034b0817408190817e4a3ee0003d57 |
completed | May 12, 2026, 3:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a034bdf5c808190ac329e663e220f1b |
completed | May 12, 2026, 3:48 p.m. |
Created at: April 10, 2026, 10:25 a.m.