Triple
T15985674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All American |
E387685
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
AA
AA is the common abbreviation for "All American," a term often used in the United States to denote exemplary athletes, products, or qualities that embody traditional American ideals.
|
E1187863
|
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: AA | Statement: [All American, hasAbbreviation, AA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AA Context triple: [All American, hasAbbreviation, AA]
-
A.
AA
AA is the two-letter IATA airline designator used to identify American Airlines in flight schedules, tickets, and aviation systems.
-
B.
AA
AA was the common abbreviation for the German Foreign Office (Auswärtiges Amt) during the Nazi era.
-
C.
AA
AA is a UK welfare benefit that provides financial support to older people who need help with personal care due to illness or disability.
-
D.
AA
AA is the common abbreviation for Arthur Andersen, the former Big Five accounting firm that collapsed following its involvement in the Enron scandal.
-
E.
AA
AA is the New York Stock Exchange ticker symbol for Alcoa Corporation, a major American producer of aluminum and related products.
- 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: AA Triple: [All American, hasAbbreviation, AA]
Generated description
AA is the common abbreviation for "All American," a term often used in the United States to denote exemplary athletes, products, or qualities that embody traditional American ideals.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AA Target entity description: AA is the common abbreviation for "All American," a term often used in the United States to denote exemplary athletes, products, or qualities that embody traditional American ideals.
-
A.
AA
AA is the two-letter IATA airline designator used to identify American Airlines in flight schedules, tickets, and aviation systems.
-
B.
AA
AA is the common abbreviation for Arthur Andersen, the former Big Five accounting firm that collapsed following its involvement in the Enron scandal.
-
C.
AA
AA is the commonly used short form for Stanford University's Aeronautics and Astronautics Department, which focuses on aerospace engineering education and research.
-
D.
AA
AA is the standard abbreviation for the Second Vatican Council document *Apostolicam Actuositatem*, which outlines the role and mission of laypeople in the Catholic Church.
-
E.
AA
AA was the common abbreviation for the German Foreign Office (Auswärtiges Amt) during the Nazi era.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157589d78819091f7b9b1081dd6ad |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3cfc8d08190a02abc90c889c8e1 |
completed | May 9, 2026, 11:31 p.m. |
| NEDg | Description generation | batch_69ffc4ed71648190983a0a4150c4d8c4 |
completed | May 9, 2026, 11:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffc5a5b46881908589fd1dabef5378 |
completed | May 9, 2026, 11:39 p.m. |
Created at: April 10, 2026, 4:54 a.m.