Triple
T10411945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DC SFRA |
E245412
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | TSA |
E17140
|
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: TSA | Statement: [DC SFRA, associatedWith, TSA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TSA Context triple: [DC SFRA, associatedWith, TSA]
-
A.
TSA
TSA is the IATA airport code for Taipei Songshan Airport, a major domestic and regional airport serving Taipei, Taiwan.
-
B.
TSA
TSA is the vehicle registration code assigned to Sandomierz County in Poland.
-
C.
Transportation Security Administration
chosen
The Transportation Security Administration (TSA) is a U.S. federal agency responsible for ensuring the security of the nation’s transportation systems, most notably through passenger and baggage screening at airports.
-
D.
TSA Pre✓
TSA Pre✓ is a U.S. Transportation Security Administration program that offers expedited airport security screening for pre-approved, low-risk travelers.
-
E.
وزارة الطيران المدني
وزارة الطيران المدني هي الجهة الحكومية المصرية المسؤولة عن تنظيم وإدارة شؤون الطيران المدني والمطارات والنقل الجوي في مصر.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9fc72d081908d81c71133973daf |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fbfae96c8190ac496e9a1158afe4 |
completed | April 9, 2026, 7:20 p.m. |
Created at: April 6, 2026, 12:10 p.m.