Triple
T5248743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AstraZeneca |
E118527
|
entity |
| Predicate | tickerSymbol |
P1447
|
FINISHED |
| Object |
AZN
AZN is the stock ticker symbol for AstraZeneca, a major global biopharmaceutical company known for developing prescription medicines across several therapeutic areas.
|
E505477
|
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: AZN | Statement: [AstraZeneca, tickerSymbol, AZN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AZN Context triple: [AstraZeneca, tickerSymbol, AZN]
-
A.
AZN
AZN is the IATA airport code for Andijan Airport, a regional air transport hub serving the city of Andijan in eastern Uzbekistan.
-
B.
AZU
AZU is the ICAO airline designator for Azul Brazilian Airlines, a major low-cost carrier based in Brazil.
-
C.
AZD
AZD is a common shorthand used to refer to the Arizona Diamondbacks, a Major League Baseball team based in Phoenix, Arizona.
-
D.
AZO
AZO is the stock ticker symbol for AutoZone, a major American retailer and distributor of automotive replacement parts and accessories.
-
E.
ZAZ
ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
- 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: AZN Triple: [AstraZeneca, tickerSymbol, AZN]
Generated description
AZN is the stock ticker symbol for AstraZeneca, a major global biopharmaceutical company known for developing prescription medicines across several therapeutic areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AZN Target entity description: AZN is the stock ticker symbol for AstraZeneca, a major global biopharmaceutical company known for developing prescription medicines across several therapeutic areas.
-
A.
AZN
AZN is the IATA airport code for Andijan Airport, a regional air transport hub serving the city of Andijan in eastern Uzbekistan.
-
B.
AZU
AZU is the ICAO airline designator for Azul Brazilian Airlines, a major low-cost carrier based in Brazil.
-
C.
AZD
AZD is a common shorthand used to refer to the Arizona Diamondbacks, a Major League Baseball team based in Phoenix, Arizona.
-
D.
AZO
AZO is the stock ticker symbol for AutoZone, a major American retailer and distributor of automotive replacement parts and accessories.
-
E.
ZAZ
ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
- 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_69bd4468aacc8190a8196f71855cdf4f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b787b34819081af96de9355bb4f |
completed | March 20, 2026, 4:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef83998f881909fef2746f5c496af |
completed | March 21, 2026, 7:57 p.m. |
| NEDg | Description generation | batch_69befa746be88190a8d807317ab36430 |
completed | March 21, 2026, 8:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69befac54e8c8190986aca0f5591d04e |
completed | March 21, 2026, 8:08 p.m. |
Created at: March 20, 2026, 1:50 p.m.