Triple
T10543037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haut-Ogooué Province |
E248743
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Bongoville
Bongoville is a town in southeastern Gabon known as the birthplace of former Gabonese president Omar Bongo.
|
E871354
|
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: Bongoville | Statement: [Haut-Ogooué Province, containsCity, Bongoville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bongoville Context triple: [Haut-Ogooué Province, containsCity, Bongoville]
-
A.
Bompoka
Bompoka is a small, remote island that forms part of India’s Nicobar Islands archipelago in the eastern Indian Ocean.
-
B.
Badaguan
Badaguan is a scenic coastal area in Qingdao famous for its tree-lined streets, historic European-style villas, and popular seaside promenades.
-
C.
Baguia
Baguia is a remote mountainous region and administrative post in eastern Timor-Leste known for its traditional villages and rugged landscapes.
-
D.
Bogoso
Bogoso is a mining town in southwestern Ghana known for its significant gold deposits and related industrial activities.
-
E.
Rokovoko
Rokovoko is the fictional, remote South Pacific island homeland of Queequeg in Herman Melville’s novel "Moby-Dick."
- 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: Bongoville Triple: [Haut-Ogooué Province, containsCity, Bongoville]
Generated description
Bongoville is a town in southeastern Gabon known as the birthplace of former Gabonese president Omar Bongo.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bongoville Target entity description: Bongoville is a town in southeastern Gabon known as the birthplace of former Gabonese president Omar Bongo.
-
A.
Bompoka
Bompoka is a small, remote island that forms part of India’s Nicobar Islands archipelago in the eastern Indian Ocean.
-
B.
Badaguan
Badaguan is a scenic coastal area in Qingdao famous for its tree-lined streets, historic European-style villas, and popular seaside promenades.
-
C.
Baguia
Baguia is a remote mountainous region and administrative post in eastern Timor-Leste known for its traditional villages and rugged landscapes.
-
D.
Bogoso
Bogoso is a mining town in southwestern Ghana known for its significant gold deposits and related industrial activities.
-
E.
Rokovoko
Rokovoko is the fictional, remote South Pacific island homeland of Queequeg in Herman Melville’s novel "Moby-Dick."
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5190f46d08190a92b1191881ffb92 |
completed | April 7, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9342e6cf48190b0ca53ff2a4e0214 |
completed | April 10, 2026, 5:32 p.m. |
| NEDg | Description generation | batch_69d938c697f481908a93296ee7f82eae |
completed | April 10, 2026, 5:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d940176c988190b7583ce9f2c21898 |
completed | April 10, 2026, 6:23 p.m. |
Created at: April 6, 2026, 12:32 p.m.