Triple
T6038858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Child of Fortune |
E134489
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Moussa
Moussa is the protagonist of the work "Child of Fortune," around whom the story’s central events and character development revolve.
|
E564675
|
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: Moussa | Statement: [Child of Fortune, mainCharacter, Moussa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moussa Context triple: [Child of Fortune, mainCharacter, Moussa]
-
A.
Idrissa
Idrissa is the given first name of British actor, producer, and musician Idris Elba.
-
B.
Musa
Musa is the name used in the Quran for the prophet Moses, a central figure in Islamic tradition known for leading the Israelites and receiving divine revelation.
-
C.
Musa
Musa is a central character in Arundhati Roy’s novel "The Ministry of Utmost Happiness," around whom key political and personal conflicts in Kashmir revolve.
-
D.
Djiba
Djiba is a locality in the Ituri region of the Democratic Republic of the Congo, known as the birthplace of militia leader Thomas Lubanga Dyilo.
-
E.
Mansa
Mansa is a city in the Malwa region of Punjab, India, known primarily as an agricultural and cotton-growing center.
- 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: Moussa Triple: [Child of Fortune, mainCharacter, Moussa]
Generated description
Moussa is the protagonist of the work "Child of Fortune," around whom the story’s central events and character development revolve.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Moussa Target entity description: Moussa is the protagonist of the work "Child of Fortune," around whom the story’s central events and character development revolve.
-
A.
Idrissa
Idrissa is the given first name of British actor, producer, and musician Idris Elba.
-
B.
Musa
Musa is the name used in the Quran for the prophet Moses, a central figure in Islamic tradition known for leading the Israelites and receiving divine revelation.
-
C.
Musa
Musa is a central character in Arundhati Roy’s novel "The Ministry of Utmost Happiness," around whom key political and personal conflicts in Kashmir revolve.
-
D.
Djiba
Djiba is a locality in the Ituri region of the Democratic Republic of the Congo, known as the birthplace of militia leader Thomas Lubanga Dyilo.
-
E.
Mansa
Mansa is a city in the Malwa region of Punjab, India, known primarily as an agricultural and cotton-growing center.
- 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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056ce10cc8190817ade56570adc92 |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11393f4ec81909f175de55694b44e |
completed | March 23, 2026, 10:19 a.m. |
| NEDg | Description generation | batch_69c11560824081909d1228056607a3bd |
completed | March 23, 2026, 10:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c11607805c8190a9bc734479b1cb8d |
completed | March 23, 2026, 10:29 a.m. |
Created at: March 22, 2026, 4:08 p.m.