Triple
T662602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faro Airport |
E11788
|
entity |
| Predicate | cityServed |
P82
|
FINISHED |
| Object |
Faro
Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
|
E84088
|
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: Faro | Statement: [Faro Airport, cityServed, Faro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faro Context triple: [Faro Airport, cityServed, Faro]
-
A.
Køpmannæhafn
Køpmannæhafn is the historical Danish name for the city now known as Copenhagen, reflecting its origins as a merchant harbor.
-
B.
Hvalsey
Hvalsey is the best-preserved Norse ruin site in Greenland, known for its stone church and remnants of a medieval farming settlement.
-
C.
Grytviken
Grytviken is a former whaling station and now-abandoned settlement on the island of South Georgia, notable for its historical role in Antarctic exploration and as the burial place of Ernest Shackleton.
-
D.
Arendal
Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
-
E.
Faro Airport
Faro Airport is the main international airport serving Portugal’s Algarve region, handling millions of tourists each year who visit its popular coastal resorts.
- 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: Faro Triple: [Faro Airport, cityServed, Faro]
Generated description
Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Faro Target entity description: Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
-
A.
Køpmannæhafn
Køpmannæhafn is the historical Danish name for the city now known as Copenhagen, reflecting its origins as a merchant harbor.
-
B.
Hvalsey
Hvalsey is the best-preserved Norse ruin site in Greenland, known for its stone church and remnants of a medieval farming settlement.
-
C.
Grytviken
Grytviken is a former whaling station and now-abandoned settlement on the island of South Georgia, notable for its historical role in Antarctic exploration and as the burial place of Ernest Shackleton.
-
D.
Arendal
Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
-
E.
Faro Airport
Faro Airport is the main international airport serving Portugal’s Algarve region, handling millions of tourists each year who visit its popular coastal resorts.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fd081e8819097f289961f5eff29 |
completed | March 1, 2026, 8:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5dc9b645881908c7d2d69aa2f44aa |
completed | March 2, 2026, 6:53 p.m. |
| NEDg | Description generation | batch_69a5e63dbd488190a2cd3c241cc76465 |
completed | March 2, 2026, 7:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a601c3b8f081908e821092ca9cfc82 |
completed | March 2, 2026, 9:31 p.m. |
Created at: March 1, 2026, 7:36 p.m.