Triple
T21255357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Muma |
E523853
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Les Muma |
—
|
NE NERFINISHED |
How this triple was built (2 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: Les Muma | Statement: [Les Muma, name, Les Muma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Les Muma Context triple: [Les Muma, name, Les Muma]
-
A.
Les Muma
chosen
Les Muma is an American businessman and philanthropist best known for his major contributions to the University of South Florida, where the business school bears his name.
-
B.
Maamme
Maamme is the national anthem of Finland, known for its patriotic lyrics and prominent role in Finnish national ceremonies and sporting events.
-
C.
Mamatid
Mamatid is a barangay in Cabuyao, Laguna, Philippines, known for hosting the southern terminus of the PNR Metro Commuter Line.
-
D.
La Nana
La Nana is a critically acclaimed Chilean drama film that follows the emotional journey of a long-serving maid whose life is upended when her employers hire additional help.
-
E.
La MaMa
La MaMa is a renowned Off-Off-Broadway experimental theater in New York City known for fostering avant-garde performance and emerging artists.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735a0e7dc8190b591b5b6786ce619 |
completed | April 21, 2026, 8:30 a.m. |
Created at: April 16, 2026, 3:58 p.m.