Triple
T8932895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bong County |
E212699
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Totota
Totota is a town located in Bong County in central Liberia.
|
E767824
|
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: Totota | Statement: [Bong County, hasTown, Totota]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Totota Context triple: [Bong County, hasTown, Totota]
-
A.
Datsun
Datsun is a historic Japanese automobile brand, revived as a budget-focused marque under the Renault–Nissan–Mitsubishi Alliance and known for its small, affordable cars.
-
B.
Mobil
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
-
C.
Azuga
Azuga is a small mountain resort town in Romania known for its ski slopes and scenic location in the Carpathian Mountains.
-
D.
Datsun Cherry
The Datsun Cherry was a compact front-wheel-drive car produced by Nissan in the 1970s and early 1980s, known as one of the company’s early global small cars.
-
E.
Toyota Kluger
The Toyota Kluger is a mid-size crossover SUV produced by Toyota, marketed in various regions as a comfortable, family-oriented vehicle with three-row seating.
- 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: Totota Triple: [Bong County, hasTown, Totota]
Generated description
Totota is a town located in Bong County in central Liberia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Totota Target entity description: Totota is a town located in Bong County in central Liberia.
-
A.
Datsun
Datsun is a historic Japanese automobile brand, revived as a budget-focused marque under the Renault–Nissan–Mitsubishi Alliance and known for its small, affordable cars.
-
B.
Mobil
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
-
C.
Azuga
Azuga is a small mountain resort town in Romania known for its ski slopes and scenic location in the Carpathian Mountains.
-
D.
Datsun Cherry
The Datsun Cherry was a compact front-wheel-drive car produced by Nissan in the 1970s and early 1980s, known as one of the company’s early global small cars.
-
E.
Toyota Kluger
The Toyota Kluger is a mid-size crossover SUV produced by Toyota, marketed in various regions as a comfortable, family-oriented vehicle with three-row seating.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc668e5c108190b08f9cd6b4fd4a8b |
completed | April 1, 2026, 12:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc1d965cc8190bad0a990df318698 |
completed | April 3, 2026, 1:34 p.m. |
| NEDg | Description generation | batch_69cfc3b3044c81908631fee4ffe5c25f |
completed | April 3, 2026, 1:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfc41fca3081908d8c2515c98283de |
completed | April 3, 2026, 1:43 p.m. |
Created at: March 30, 2026, 6:57 p.m.