Triple
T661400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Orly Airport |
E11762
|
entity |
| Predicate | IATA code |
P2569
|
FINISHED |
| Object | ORY |
E10907
|
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: ORY | Statement: [Paris Orly Airport, IATA code, ORY]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ORY Context triple: [Paris Orly Airport, IATA code, ORY]
-
A.
ORY
chosen
ORY is the three-letter IATA airport code for Paris Orly Airport, a major international airport serving the Paris metropolitan area in France.
-
B.
OR
OR is the official two-letter United States Postal Service abbreviation for the state of Oregon.
-
C.
WR
WR is the abbreviation for the German Council of Science and Humanities, a key advisory body that counsels the German federal and state governments on science, research, and higher education policy.
-
D.
RE
RE is the common abbreviation for the British Army’s Corps of Royal Engineers, responsible for military engineering and technical support.
-
E.
REN
REN is a blockchain-based project and protocol focused on enabling cross-chain liquidity and interoperability between different cryptocurrency networks.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fa954988190841740a587ace466 |
completed | March 1, 2026, 8:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5c3963c588190b7116f3f7aad2687 |
completed | March 2, 2026, 5:06 p.m. |
Created at: March 1, 2026, 7:36 p.m.