Triple
T11348806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DC Motema Pembe |
E268788
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
Motema Pembe
Motema Pembe is a football club from the Democratic Republic of the Congo, known for its success in domestic competitions and participation in African continental tournaments.
|
E920215
|
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: Motema Pembe | Statement: [DC Motema Pembe, shortName, Motema Pembe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Motema Pembe Context triple: [DC Motema Pembe, shortName, Motema Pembe]
-
A.
Gule
Gule is a lesser-known language belonging to the Koman group of languages spoken in the border regions of Ethiopia and Sudan.
-
B.
Premikudu
Premikudu is the Telugu-dubbed version of the popular 1994 Tamil romantic action film "Kadhalan," starring Prabhu Deva and Nagma and directed by Shankar.
-
C.
Mishanya
Mishanya is a Russian diminutive nickname commonly used for the male given name Mikhail.
-
D.
Velvet Brown
Velvet Brown is the determined young English girl who dreams of racing her beloved horse to victory in the classic novel and film "National Velvet."
-
E.
The Magenta
The Magenta was the original name of The Harvard Crimson, the daily student newspaper of Harvard University.
- 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: Motema Pembe Triple: [DC Motema Pembe, shortName, Motema Pembe]
Generated description
Motema Pembe is a football club from the Democratic Republic of the Congo, known for its success in domestic competitions and participation in African continental tournaments.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Motema Pembe Target entity description: Motema Pembe is a football club from the Democratic Republic of the Congo, known for its success in domestic competitions and participation in African continental tournaments.
-
A.
Gule
Gule is a lesser-known language belonging to the Koman group of languages spoken in the border regions of Ethiopia and Sudan.
-
B.
Premikudu
Premikudu is the Telugu-dubbed version of the popular 1994 Tamil romantic action film "Kadhalan," starring Prabhu Deva and Nagma and directed by Shankar.
-
C.
Mishanya
Mishanya is a Russian diminutive nickname commonly used for the male given name Mikhail.
-
D.
Velvet Brown
Velvet Brown is the determined young English girl who dreams of racing her beloved horse to victory in the classic novel and film "National Velvet."
-
E.
The Magenta
The Magenta was the original name of The Harvard Crimson, the daily student newspaper of Harvard University.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea23391c819089e8f9725cb3a0ff |
completed | April 9, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5438d7b58819093cc1407fefe8ab5 |
completed | April 19, 2026, 9:05 p.m. |
| NEDg | Description generation | batch_69e548bb7be4819093aeeaf0c048033e |
completed | April 19, 2026, 9:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e54eeba4a88190af128a99c277853a |
completed | April 19, 2026, 9:53 p.m. |
Created at: April 8, 2026, 9:33 p.m.