Triple
T5746241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ali |
E126738
|
entity |
| Predicate | transliterationSystem |
P5923
|
FINISHED |
| Object |
ALA-LC
ALA-LC is a widely used romanization standard developed by the American Library Association and the Library of Congress for converting non-Latin scripts into the Latin alphabet for cataloging and bibliographic purposes.
|
E364120
|
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: ALA-LC | Statement: [Ali, transliterationSystem, ALA-LC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ALA-LC Context triple: [Ali, transliterationSystem, ALA-LC]
-
A.
ALA (historical)
ALA (historical) was the former stock ticker symbol used to represent the French telecommunications company Alcatel on securities exchanges.
-
B.
ALA
ALA is the leading professional organization in the United States dedicated to supporting libraries, librarians, and information services.
-
C.
ALA
ALA is the three-letter ISO 3166-1 country code assigned to the autonomous Åland Islands region of Finland.
-
D.
ALA
ALA is the IATA airport code for Almaty International Airport, the main air gateway to Almaty, Kazakhstan.
-
E.
LCC
LCC is a comprehensive library classification system developed by the Library of Congress to organize and arrange books and other materials by subject.
- 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: ALA-LC Triple: [Ali, transliterationSystem, ALA-LC]
Generated description
ALA-LC is a widely used romanization standard developed by the American Library Association and the Library of Congress for converting non-Latin scripts into the Latin alphabet for cataloging and bibliographic purposes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ALA-LC Target entity description: ALA-LC is a widely used romanization standard developed by the American Library Association and the Library of Congress for converting non-Latin scripts into the Latin alphabet for cataloging and bibliographic purposes.
-
A.
ALA (historical)
ALA (historical) was the former stock ticker symbol used to represent the French telecommunications company Alcatel on securities exchanges.
-
B.
ALA
chosen
ALA is the leading professional organization in the United States dedicated to supporting libraries, librarians, and information services.
-
C.
ALA
ALA is the IATA airport code for Almaty International Airport, the main air gateway to Almaty, Kazakhstan.
-
D.
ALA
ALA is the three-letter ISO 3166-1 country code assigned to the autonomous Åland Islands region of Finland.
-
E.
LCC
LCC is a comprehensive library classification system developed by the Library of Congress to organize and arrange books and other materials by subject.
- F. None of above.
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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c025896378819085f0bd43bf34f497 |
completed | March 22, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e2c54c0819087ab79ae855b9677 |
completed | March 22, 2026, 11:41 p.m. |
| NEDg | Description generation | batch_69c08cc5c48481909c1ac21d586b3263 |
completed | March 23, 2026, 12:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c08d42cac88190b6cd454e8c31a4ef |
completed | March 23, 2026, 12:45 a.m. |
Created at: March 22, 2026, 3:48 p.m.