Triple
T14037498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lobito |
E337749
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object |
Benguela
Benguela is a coastal city in western Angola known historically as a major port and trading center on the South Atlantic.
|
E1075076
|
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: Benguela | Statement: [Lobito, nearbyCity, Benguela]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benguela Context triple: [Lobito, nearbyCity, Benguela]
-
A.
Ovambo
Ovambo is a Bantu language spoken primarily by the Ovambo people in northern Namibia and southern Angola.
-
B.
Assosa
Assosa is a town in western Ethiopia that serves as the administrative and economic center of the Benishangul-Gumuz Region near the Sudanese border.
-
C.
Beira Lake
Beira Lake is a prominent urban lake in central Colombo, Sri Lanka, known for its scenic views, religious sites, and recreational activities amid the city’s commercial district.
-
D.
Río de Oro
Río de Oro was a former Spanish colonial territory in northwest Africa that later became part of the disputed region of Western Sahara.
-
E.
Río de Oro
Río de Oro is a river in northeastern Colombia that flows through the Santander region and passes near the city of Bucaramanga.
- 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: Benguela Triple: [Lobito, nearbyCity, Benguela]
Generated description
Benguela is a coastal city in western Angola known historically as a major port and trading center on the South Atlantic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Benguela Target entity description: Benguela is a coastal city in western Angola known historically as a major port and trading center on the South Atlantic.
-
A.
Ovambo
Ovambo is a Bantu language spoken primarily by the Ovambo people in northern Namibia and southern Angola.
-
B.
Assosa
Assosa is a town in western Ethiopia that serves as the administrative and economic center of the Benishangul-Gumuz Region near the Sudanese border.
-
C.
Beira Lake
Beira Lake is a prominent urban lake in central Colombo, Sri Lanka, known for its scenic views, religious sites, and recreational activities amid the city’s commercial district.
-
D.
Río de Oro
Río de Oro was a former Spanish colonial territory in northwest Africa that later became part of the disputed region of Western Sahara.
-
E.
Río de Oro
Río de Oro is a river in northeastern Colombia that flows through the Santander region and passes near the city of Bucaramanga.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de30e312148190a6be0a3258364e6e |
completed | April 14, 2026, 12:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc33bc20081909abea7e64d1bd578 |
completed | May 6, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69fbc53729d081908b74532d2ed54b7a |
completed | May 6, 2026, 10:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fbc5d76cdc8190970778580437cf72 |
completed | May 6, 2026, 10:51 p.m. |
Created at: April 9, 2026, 10:20 p.m.