Triple
T12759653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Narciso |
E304956
|
entity |
| Predicate | connectedToCharacter |
P37306
|
FINISHED |
| Object | Mucho Maas |
E305352
|
NE FINISHED |
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: Mucho Maas | Statement: [San Narciso, connectedToCharacter, Mucho Maas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mucho Maas Context triple: [San Narciso, connectedToCharacter, Mucho Maas]
-
A.
Mucho Maas
chosen
Mucho Maas is a troubled California disc jockey and the husband of protagonist Oedipa Maas in Thomas Pynchon's novel "The Crying of Lot 49."
-
B.
Maashees
Maashees is a small village in the Dutch province of North Brabant, situated along the river Meuse and known for its rural character and historic church.
-
C.
Mazama temama
Mazama temama, commonly known as the Central American red brocket, is a small, elusive deer species native to the tropical forests of Central America and parts of southern Mexico.
-
D.
Maamme
Maamme is the national anthem of Finland, known for its patriotic lyrics and prominent role in Finnish national ceremonies and sporting events.
-
E.
Maatkas
Maatkas is a town and commune located in the mountainous Kabylie region of northern Algeria.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8d3eb08190ae998df5cc6d9ba6 |
completed | April 10, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c9c93248190b77c7d229da64ffb |
completed | May 2, 2026, 10:37 p.m. |
Created at: April 9, 2026, 5:28 p.m.