Triple
T19385025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AAA |
E484910
|
entity |
| Predicate | contrastedWith |
P278
|
FINISHED |
| Object | AA |
—
|
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: AA | Statement: [AAA, contrastedWith, AA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AA Context triple: [AAA, contrastedWith, 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.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b3ffa548190a060d6e94562a5d2 |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 10, 2026, 1:35 p.m.