Triple
T107644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orly Airport |
E2174
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
ORY
ORY is the three-letter IATA airport code for Paris Orly Airport, a major international airport serving the Paris metropolitan area in France.
|
E10907
|
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: ORY | Statement: [Orly Airport, IATAcode, ORY]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ORY Context triple: [Orly Airport, IATAcode, ORY]
-
A.
OR
OR is the official two-letter United States Postal Service abbreviation for the state of Oregon.
-
B.
You
"You" refers to the collective community of internet users whose user-generated content and online collaboration transformed media, culture, and communication in the digital age.
-
C.
OM
OM is the post-nominal abbreviation used by members of the Order of Merit, a prestigious British honor recognizing distinguished service in the armed forces, science, art, literature, or the promotion of culture.
-
D.
GU
GU is the two-letter ISO 3166 country code assigned to Guam, an unincorporated territory of the United States in the western Pacific Ocean.
-
E.
W
W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
- 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: ORY Triple: [Orly Airport, IATAcode, ORY]
Generated description
ORY is the three-letter IATA airport code for Paris Orly Airport, a major international airport serving the Paris metropolitan area in France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ORY Target entity description: ORY is the three-letter IATA airport code for Paris Orly Airport, a major international airport serving the Paris metropolitan area in France.
-
A.
OR
OR is the official two-letter United States Postal Service abbreviation for the state of Oregon.
-
B.
You
"You" refers to the collective community of internet users whose user-generated content and online collaboration transformed media, culture, and communication in the digital age.
-
C.
OM
OM is the post-nominal abbreviation used by members of the Order of Merit, a prestigious British honor recognizing distinguished service in the armed forces, science, art, literature, or the promotion of culture.
-
D.
GU
GU is the two-letter ISO 3166 country code assigned to Guam, an unincorporated territory of the United States in the western Pacific Ocean.
-
E.
W
W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a256cac6d4819083b50c9c9d95e975 |
completed | Feb. 28, 2026, 2:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a275e81aa48190827b634822e25058 |
completed | Feb. 28, 2026, 4:58 a.m. |
| NEDg | Description generation | batch_69a2772d526881909052faae2b3b9829 |
completed | Feb. 28, 2026, 5:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a277a7c6a08190820993e8de80d21a |
completed | Feb. 28, 2026, 5:05 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.