Triple
T16009739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Malone |
E388306
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object |
the Mulefa
The Mulefa are a fictional species from Philip Pullman’s His Dark Materials universe, known for their diamond-framed bodies, use of seed-pod wheels, and deep, symbiotic connection to the substance called Dust.
|
E1189669
|
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: the Mulefa | Statement: [Mary Malone, associatedWith, the Mulefa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: the Mulefa Context triple: [Mary Malone, associatedWith, the Mulefa]
-
A.
Mulee'aage
Mulee'aage is the official presidential palace and primary residence of the President of the Maldives, located in the capital city Malé.
-
B.
Mungava
Mungava is an alternative name for Bellona Island, a small inhabited island in the Solomon Islands in the South Pacific.
-
C.
Mugatu
Mugatu is the flamboyant, villainous fashion designer portrayed by Will Ferrell in the comedy film "Zoolander."
-
D.
Mwaghavul
Mwaghavul is a Chadic language spoken primarily by the Mwaghavul people in Plateau State, central Nigeria.
-
E.
Mungaka
Mungaka is a Grassfields Bantu language spoken primarily in Cameroon, particularly associated with the Bamunka (Ndop) area.
- 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: the Mulefa Triple: [Mary Malone, associatedWith, the Mulefa]
Generated description
The Mulefa are a fictional species from Philip Pullman’s His Dark Materials universe, known for their diamond-framed bodies, use of seed-pod wheels, and deep, symbiotic connection to the substance called Dust.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: the Mulefa Target entity description: The Mulefa are a fictional species from Philip Pullman’s His Dark Materials universe, known for their diamond-framed bodies, use of seed-pod wheels, and deep, symbiotic connection to the substance called Dust.
-
A.
Mulee'aage
Mulee'aage is the official presidential palace and primary residence of the President of the Maldives, located in the capital city Malé.
-
B.
Mungava
Mungava is an alternative name for Bellona Island, a small inhabited island in the Solomon Islands in the South Pacific.
-
C.
Mugatu
Mugatu is the flamboyant, villainous fashion designer portrayed by Will Ferrell in the comedy film "Zoolander."
-
D.
Mwaghavul
Mwaghavul is a Chadic language spoken primarily by the Mwaghavul people in Plateau State, central Nigeria.
-
E.
Mungaka
Mungaka is a Grassfields Bantu language spoken primarily in Cameroon, particularly associated with the Bamunka (Ndop) area.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1828f8c688190a6b365f9140cd2d8 |
completed | April 17, 2026, 12:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf24a9d8819083d7b11d71442da6 |
completed | May 10, 2026, 12:19 a.m. |
| NEDg | Description generation | batch_69ffd065cb948190b0ad7e89a12ce535 |
completed | May 10, 2026, 12:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffd1a52de08190a7b283af83be1f42 |
completed | May 10, 2026, 12:30 a.m. |
Created at: April 10, 2026, 4:55 a.m.