Triple
T9257859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ha'il Regional Airport |
E222490
|
entity |
| Predicate | IATA code |
P2569
|
FINISHED |
| Object |
HAS
HAS is the IATA airport code for Ha'il Regional Airport in Ha'il, Saudi Arabia.
|
E788905
|
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: HAS | Statement: [Ha'il Regional Airport, IATA code, HAS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HAS Context triple: [Ha'il Regional Airport, IATA code, HAS]
-
A.
HAS
HAS is the stock ticker symbol for Hasbro, Inc., a major American toy and entertainment company traded on the NASDAQ.
-
B.
HAV
HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
-
C.
HASP
HASP (Houston Automatic Spooling Priority) was an early IBM mainframe job entry and spooling system that managed batch workloads and printer output, serving as a foundation for later systems like JES2.
-
D.
AH
AH is a German vehicle registration code associated with the town of Alstätte.
-
E.
HAD
HAD is the station code used to identify Hallunda metro station in the Stockholm Metro system.
- 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: HAS Triple: [Ha'il Regional Airport, IATA code, HAS]
Generated description
HAS is the IATA airport code for Ha'il Regional Airport in Ha'il, Saudi Arabia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HAS Target entity description: HAS is the IATA airport code for Ha'il Regional Airport in Ha'il, Saudi Arabia.
-
A.
HAS
HAS is the stock ticker symbol for Hasbro, Inc., a major American toy and entertainment company traded on the NASDAQ.
-
B.
HAV
HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
-
C.
HASP
HASP (Houston Automatic Spooling Priority) was an early IBM mainframe job entry and spooling system that managed batch workloads and printer output, serving as a foundation for later systems like JES2.
-
D.
AH
AH is a German vehicle registration code associated with the town of Alstätte.
-
E.
HAD
HAD is the station code used to identify Hallunda metro station in the Stockholm Metro system.
- 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_69ca841e4cd481908e738c74e958eaea |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd06b660448190b6bc04beff0f5512 |
completed | April 1, 2026, 11:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d09bf225608190ade085302946dd8f |
completed | April 4, 2026, 5:04 a.m. |
| NEDg | Description generation | batch_69d09dc3ccb08190a70e278a67249070 |
completed | April 4, 2026, 5:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d09e3f211c819087b9e75f0d8faf93 |
completed | April 4, 2026, 5:14 a.m. |
Created at: March 30, 2026, 7:32 p.m.