Triple
T4184832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nadi–Singapore |
E88284
|
entity |
| Predicate | hasICAOCodeForEndpoint |
P36333
|
FINISHED |
| Object |
WSSS
WSSS is the ICAO airport code for Singapore Changi Airport, one of the world’s busiest and most highly rated international air hubs.
|
E418864
|
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: WSSS | Statement: [Nadi–Singapore, hasICAOCodeForEndpoint, WSSS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WSSS Context triple: [Nadi–Singapore, hasICAOCodeForEndpoint, WSSS]
-
A.
HSSS
HSSS is the ICAO airport code for Khartoum International Airport, the main international gateway to Sudan’s capital city.
-
B.
ZSSS
ZSSS is the ICAO airport code for Shanghai Hongqiao International Airport, a major domestic and regional aviation hub in Shanghai, China.
-
C.
SWW
SWW is the common abbreviation for the Schwenninger Wild Wings, a professional ice hockey team based in Schwenningen, Germany.
-
D.
WST
WST is the commonly used abbreviation for the World Snooker Tour, the professional circuit for elite snooker players worldwide.
-
E.
SSV
SSV is a lightweight, off-road side-by-side vehicle class commonly used in rally raid competitions for its agility and versatility over rough terrain.
- 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: WSSS Triple: [Nadi–Singapore, hasICAOCodeForEndpoint, WSSS]
Generated description
WSSS is the ICAO airport code for Singapore Changi Airport, one of the world’s busiest and most highly rated international air hubs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: WSSS Target entity description: WSSS is the ICAO airport code for Singapore Changi Airport, one of the world’s busiest and most highly rated international air hubs.
-
A.
HSSS
HSSS is the ICAO airport code for Khartoum International Airport, the main international gateway to Sudan’s capital city.
-
B.
ZSSS
ZSSS is the ICAO airport code for Shanghai Hongqiao International Airport, a major domestic and regional aviation hub in Shanghai, China.
-
C.
SWW
SWW is the common abbreviation for the Schwenninger Wild Wings, a professional ice hockey team based in Schwenningen, Germany.
-
D.
WST
WST is the commonly used abbreviation for the World Snooker Tour, the professional circuit for elite snooker players worldwide.
-
E.
SSV
SSV is a lightweight, off-road side-by-side vehicle class commonly used in rally raid competitions for its agility and versatility over rough terrain.
- 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_69aed9477e8c81908bcb862d2db55b1d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0b2db368819080c1d652b4acfd0c |
completed | March 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b589fe4b508190a1c5a1d426245ede |
completed | March 14, 2026, 4:17 p.m. |
| NEDg | Description generation | batch_69b58a64e67081909d9c03c8f92b4f7e |
completed | March 14, 2026, 4:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b58aeb4f848190aa8d8511c3b63eaa |
completed | March 14, 2026, 4:20 p.m. |
Created at: March 9, 2026, 3:45 p.m.