Triple
T15593145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 16R/34L |
E374797
|
entity |
| Predicate | hasIATACodeAirport |
P2569
|
FINISHED |
| Object | SYD |
E8462
|
NE FINISHED |
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: SYD | Statement: [Runway 16R/34L, hasIATACodeAirport, SYD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SYD Context triple: [Runway 16R/34L, hasIATACodeAirport, SYD]
-
A.
Syd
Syd is an American singer, songwriter, producer, and founding member of the alternative R&B band The Internet, known for her smooth vocals and genre-blending sound.
-
B.
Syd
Syd is a character from the TV series "One Day at a Time," known for being Elena Alvarez's non-binary romantic partner.
-
C.
Sydney
chosen
Sydney is Australia's largest and most populous city, renowned for its iconic harbour, Opera House, and Harbour Bridge.
-
D.
Sydney
Sydney is a recurring character in Alison Bechdel’s long-running comic strip "Dykes to Watch Out For," known for her sharp intellect and complex personal relationships within its ensemble cast.
-
E.
Sydney
Sydney is the spirited, fashionable young woman who serves as the central heroine of Louisa May Alcott’s novel "An Old-Fashioned Girl."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e5e43d48190a8fd367f13f1c7e1 |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56c7db58819089cb488fb3ea96cd |
completed | May 9, 2026, 3:46 p.m. |
Created at: April 10, 2026, 4:12 a.m.