Triple
T10691490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Savannah station |
E252018
|
entity |
| Predicate | hasCode |
P9567
|
FINISHED |
| Object |
SAV
SAV is the IATA airport code for Savannah/Hilton Head International Airport serving Savannah, Georgia, and the surrounding region.
|
E878401
|
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: SAV | Statement: [Savannah station, hasCode, SAV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SAV Context triple: [Savannah station, hasCode, SAV]
-
A.
SAV
SAV is the National Rail station code for Stratford-upon-Avon railway station in Warwickshire, England.
-
B.
SAVAMA
SAVAMA was the post-revolution Iranian intelligence and security organization that succeeded the Shah’s notorious secret police, SAVAK.
-
C.
SAVC
SAVC is the ICAO airport code for General Enrique Mosconi International Airport in Comodoro Rivadavia, Argentina.
-
D.
SAVP
SAVP is a profile or configuration associated with the Real-time Transport Protocol (RTP), typically used to define specific parameters or behaviors for secure or specialized media streaming sessions.
-
E.
SAU
SAU is an international university established by the South Asian Association for Regional Cooperation (SAARC) in New Delhi, India, focusing on postgraduate and doctoral education and research for students from South Asian countries.
- 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: SAV Triple: [Savannah station, hasCode, SAV]
Generated description
SAV is the IATA airport code for Savannah/Hilton Head International Airport serving Savannah, Georgia, and the surrounding region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SAV Target entity description: SAV is the IATA airport code for Savannah/Hilton Head International Airport serving Savannah, Georgia, and the surrounding region.
-
A.
SAV
SAV is the National Rail station code for Stratford-upon-Avon railway station in Warwickshire, England.
-
B.
SAVAMA
SAVAMA was the post-revolution Iranian intelligence and security organization that succeeded the Shah’s notorious secret police, SAVAK.
-
C.
SAVC
SAVC is the ICAO airport code for General Enrique Mosconi International Airport in Comodoro Rivadavia, Argentina.
-
D.
SAVP
SAVP is a profile or configuration associated with the Real-time Transport Protocol (RTP), typically used to define specific parameters or behaviors for secure or specialized media streaming sessions.
-
E.
SAU
SAU is an international university established by the South Asian Association for Regional Cooperation (SAARC) in New Delhi, India, focusing on postgraduate and doctoral education and research for students from South Asian countries.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd3705788190bcbdef93b4c5f574 |
completed | April 9, 2026, 1:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d988ad741c8190b9ae962e0c5bc272 |
completed | April 10, 2026, 11:33 p.m. |
| NEDg | Description generation | batch_69d98aecef388190a270e92c93ccca05 |
completed | April 10, 2026, 11:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d98c04e8c08190b4d7bc63357c69f4 |
completed | April 10, 2026, 11:47 p.m. |
Created at: April 8, 2026, 9:11 p.m.