Triple
T14328663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mumbo Jumbo |
E355280
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object |
PaPa LaBas
PaPa LaBas is a trickster-like detective and hoodoo practitioner who serves as the central figure in Ishmael Reed’s satirical novel "Mumbo Jumbo."
|
E1094299
|
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: PaPa LaBas | Statement: [Mumbo Jumbo, hasMainCharacter, PaPa LaBas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PaPa LaBas Context triple: [Mumbo Jumbo, hasMainCharacter, PaPa LaBas]
-
A.
Paglat
Paglat is a municipality located in the province of Maguindanao in the southern Philippines.
-
B.
Pasamalar
Pasamalar is a classic 1961 Tamil drama film renowned for its emotional portrayal of the deep bond between a brother and sister.
-
C.
Paupisi
Paupisi is a small Italian municipality located in the Campania region, known for its rural character and proximity to the city of Benevento.
-
D.
Palapag
Palapag is a coastal municipality in the province of Northern Samar in the Philippines, known historically as a site of early Spanish-era settlements and uprisings.
-
E.
Pilcaniyeu
Pilcaniyeu is a small town in Argentina’s Patagonia region, located in the Andean area of Río Negro Province and known for its rural character and nearby natural landscapes.
- 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: PaPa LaBas Triple: [Mumbo Jumbo, hasMainCharacter, PaPa LaBas]
Generated description
PaPa LaBas is a trickster-like detective and hoodoo practitioner who serves as the central figure in Ishmael Reed’s satirical novel "Mumbo Jumbo."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PaPa LaBas Target entity description: PaPa LaBas is a trickster-like detective and hoodoo practitioner who serves as the central figure in Ishmael Reed’s satirical novel "Mumbo Jumbo."
-
A.
Paglat
Paglat is a municipality located in the province of Maguindanao in the southern Philippines.
-
B.
Pasamalar
Pasamalar is a classic 1961 Tamil drama film renowned for its emotional portrayal of the deep bond between a brother and sister.
-
C.
Paupisi
Paupisi is a small Italian municipality located in the Campania region, known for its rural character and proximity to the city of Benevento.
-
D.
Palapag
Palapag is a coastal municipality in the province of Northern Samar in the Philippines, known historically as a site of early Spanish-era settlements and uprisings.
-
E.
Pilcaniyeu
Pilcaniyeu is a small town in Argentina’s Patagonia region, located in the Andean area of Río Negro Province and known for its rural character and nearby natural landscapes.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c1c3e70819084b6728ac5c18561 |
completed | April 14, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd46927af48190b91095d852fcacbe |
completed | May 8, 2026, 2:12 a.m. |
| NEDg | Description generation | batch_69fd47fa764c8190b1d691f5847b7a05 |
completed | May 8, 2026, 2:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd492226888190a014b23e506ab19c |
completed | May 8, 2026, 2:23 a.m. |
Created at: April 10, 2026, 1:13 a.m.