Triple
T211567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tridentine Mass |
E4730
|
entity |
| Predicate | hasForm |
P169
|
FINISHED |
| Object |
Low Mass
Low Mass is a simpler, typically quieter form of the traditional Latin Tridentine Mass celebrated by a priest with minimal ceremonial and usually without music.
|
E26958
|
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: Low Mass | Statement: [Tridentine Mass, hasForm, Low Mass]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Low Mass Context triple: [Tridentine Mass, hasForm, Low Mass]
-
A.
Baixa
Baixa is Lisbon’s historic downtown district, known for its grid-planned streets, grand plazas, and Pombaline architecture rebuilt after the 1755 earthquake.
-
B.
LU
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
C.
Laz people
Laz people are an indigenous ethnic group of the South Caucasus and Black Sea coastal region, closely related to Georgians and known for their distinct Laz language and maritime culture.
-
D.
Shorter
Shorter is a surname of English origin borne by various notable individuals across different fields.
-
E.
LFPO
LFPO is the ICAO airport code for Paris Orly Airport, a major international airport serving the Paris metropolitan area in France.
- 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: Low Mass Triple: [Tridentine Mass, hasForm, Low Mass]
Generated description
Low Mass is a simpler, typically quieter form of the traditional Latin Tridentine Mass celebrated by a priest with minimal ceremonial and usually without music.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Low Mass Target entity description: Low Mass is a simpler, typically quieter form of the traditional Latin Tridentine Mass celebrated by a priest with minimal ceremonial and usually without music.
-
A.
Baixa
Baixa is Lisbon’s historic downtown district, known for its grid-planned streets, grand plazas, and Pombaline architecture rebuilt after the 1755 earthquake.
-
B.
LU
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
C.
Laz people
Laz people are an indigenous ethnic group of the South Caucasus and Black Sea coastal region, closely related to Georgians and known for their distinct Laz language and maritime culture.
-
D.
Shorter
Shorter is a surname of English origin borne by various notable individuals across different fields.
-
E.
LFPO
LFPO is the ICAO airport code for Paris Orly Airport, a major international airport serving the Paris metropolitan area in France.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c2fd0648190bae9191a84129709 |
completed | Feb. 28, 2026, 3:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a332cb28e08190a4e159b2631f5eb8 |
completed | Feb. 28, 2026, 6:24 p.m. |
| NEDg | Description generation | batch_69a333537ae481909f16bc4b37303d8c |
completed | Feb. 28, 2026, 6:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a333f5868c819083234c015ec243a5 |
completed | Feb. 28, 2026, 6:29 p.m. |
Created at: Feb. 28, 2026, 2:52 a.m.